{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from config import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2019年12月\n"
     ]
    }
   ],
   "source": [
    "print(f'{year}年{month}月')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import sys\n",
    "sys.path.append('../../py')\n",
    "import db\n",
    "import weighted\n",
    "import inspect\n",
    "import matplotlib.pyplot as plt\n",
    "import scipy.stats as stats\n",
    "import numpy as np\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_original=pd.read_sql(sql=f\"select * from _{year}{month:02} where monthly_salary>0 and monthly_salary<80000\", con=db.get_conn())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(84141, 94)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_original.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = data_original"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "del data['publish_date']\n",
    "del data['published_on_weekend']\n",
    "del data['title']\n",
    "del data['company_title']\n",
    "del data['company_description']\n",
    "del data['job_description']\n",
    "del data['job_id']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_sub_stats_by_prefix(data, prefix):\n",
    "    \n",
    "    features = [feature for feature in data.columns if feature.startswith(prefix)]\n",
    "    salary_mean=[]\n",
    "    salary_median=[]\n",
    "    salary_95_min=[]\n",
    "    salary_95_max=[]\n",
    "    count=[]\n",
    "    \n",
    "    features_out=[]\n",
    "    for feature in features:\n",
    "        #print(feature)\n",
    "        idata=data[data[feature]==1]\n",
    "        headcount=idata.headcount.sum()\n",
    "        values = idata.monthly_salary.values\n",
    "        weights = idata.headcount.values\n",
    "        #print(str(headcount))\n",
    "        if headcount==0:\n",
    "            continue\n",
    "        \n",
    "        salary_mean.append(weighted.weighted_mean(values, weights))\n",
    "        q = weighted.weighted_quantile(values,[0.025,0.5,0.975],weights)\n",
    "        salary_median.append(q[1])\n",
    "        salary_95_min.append(q[0])\n",
    "        salary_95_max.append(q[2])\n",
    "        count.append(idata.headcount.sum())\n",
    "        features_out.append(feature)\n",
    "    sub_data=pd.DataFrame()\n",
    "    sub_data['rank']=range(0,len(features_out))\n",
    "    sub_data[prefix]=[f.replace(prefix,'') for f in features_out]\n",
    "    sub_data['salary_mean']=salary_mean\n",
    "    sub_data['salary_median']=salary_median\n",
    "    sub_data['salary_95_min']=salary_95_min\n",
    "    sub_data['salary_95_max']=salary_95_max\n",
    "    sub_data['head_count']=count\n",
    "    sub_data['percentage']=count/np.sum(count)\n",
    "    sub_data=sub_data.sort_values(by='salary_mean', ascending=False)\n",
    "    sub_data['rank']=range(1,len(features_out)+1)\n",
    "    #sub_data=sub_data.reset_index()\n",
    "    return sub_data\n",
    "\n",
    "def apply_style(sub_data):\n",
    "    return sub_data.style.hide_index().format(\n",
    "        {\"percentage\":\"{:.2%}\",\"salary_mean\":\"{:.0f}\",\"salary_median\":\"{:.0f}\",\"salary_95_min\":\"{:.0f}\",\"salary_95_max\":\"{:.0f}\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_pl=get_sub_stats_by_prefix(data,'pl_')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style><table id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031ef\" ><thead>    <tr>        <th class=\"col_heading level0 col0\" >rank</th>        <th class=\"col_heading level0 col1\" >pl_</th>        <th class=\"col_heading level0 col2\" >salary_mean</th>        <th class=\"col_heading level0 col3\" >salary_median</th>        <th class=\"col_heading level0 col4\" >salary_95_min</th>        <th class=\"col_heading level0 col5\" >salary_95_max</th>        <th class=\"col_heading level0 col6\" >head_count</th>        <th class=\"col_heading level0 col7\" >percentage</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                                <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow0_col0\" class=\"data row0 col0\" >1</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow0_col1\" class=\"data row0 col1\" >rust</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow0_col2\" class=\"data row0 col2\" >20863</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow0_col3\" class=\"data row0 col3\" >17500</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow0_col4\" class=\"data row0 col4\" >4981</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow0_col5\" class=\"data row0 col5\" >58333</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow0_col6\" class=\"data row0 col6\" >436</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow0_col7\" class=\"data row0 col7\" >0.12%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow1_col0\" class=\"data row1 col0\" >2</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow1_col1\" class=\"data row1 col1\" >typescript</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow1_col2\" class=\"data row1 col2\" >18400</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow1_col3\" class=\"data row1 col3\" >22500</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow1_col4\" class=\"data row1 col4\" >6500</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow1_col5\" class=\"data row1 col5\" >27035</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow1_col6\" class=\"data row1 col6\" >1791</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow1_col7\" class=\"data row1 col7\" >0.48%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow2_col0\" class=\"data row2 col0\" >3</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow2_col1\" class=\"data row2 col1\" >go</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow2_col2\" class=\"data row2 col2\" >17883</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow2_col3\" class=\"data row2 col3\" >15500</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow2_col4\" class=\"data row2 col4\" >6000</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow2_col5\" class=\"data row2 col5\" >40000</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow2_col6\" class=\"data row2 col6\" >26931</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow2_col7\" class=\"data row2 col7\" >7.19%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow3_col0\" class=\"data row3 col0\" >4</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow3_col1\" class=\"data row3 col1\" >lua</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow3_col2\" class=\"data row3 col2\" >17865</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow3_col3\" class=\"data row3 col3\" >17500</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow3_col4\" class=\"data row3 col4\" >5250</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow3_col5\" class=\"data row3 col5\" >35000</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow3_col6\" class=\"data row3 col6\" >3160</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow3_col7\" class=\"data row3 col7\" >0.84%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow4_col0\" class=\"data row4 col0\" >5</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow4_col1\" class=\"data row4 col1\" >python</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow4_col2\" class=\"data row4 col2\" >17510</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow4_col3\" class=\"data row4 col3\" >15000</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow4_col4\" class=\"data row4 col4\" >4000</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow4_col5\" class=\"data row4 col5\" >41666</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow4_col6\" class=\"data row4 col6\" >29823</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow4_col7\" class=\"data row4 col7\" >7.96%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow5_col0\" class=\"data row5 col0\" >6</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow5_col1\" class=\"data row5 col1\" >matlab</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow5_col2\" class=\"data row5 col2\" >17401</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow5_col3\" class=\"data row5 col3\" >16000</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow5_col4\" class=\"data row5 col4\" >5013</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow5_col5\" class=\"data row5 col5\" >37500</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow5_col6\" class=\"data row5 col6\" >5622</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow5_col7\" class=\"data row5 col7\" >1.50%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow6_col0\" class=\"data row6 col0\" >7</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow6_col1\" class=\"data row6 col1\" >ruby</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow6_col2\" class=\"data row6 col2\" >17157</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow6_col3\" class=\"data row6 col3\" >16944</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow6_col4\" class=\"data row6 col4\" >3750</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow6_col5\" class=\"data row6 col5\" >37500</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow6_col6\" class=\"data row6 col6\" >1129</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow6_col7\" class=\"data row6 col7\" >0.30%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow7_col0\" class=\"data row7 col0\" >8</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow7_col1\" class=\"data row7 col1\" >haskell</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow7_col2\" class=\"data row7 col2\" >17103</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow7_col3\" class=\"data row7 col3\" >15667</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow7_col4\" class=\"data row7 col4\" >7500</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow7_col5\" class=\"data row7 col5\" >27000</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow7_col6\" class=\"data row7 col6\" >58</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow7_col7\" class=\"data row7 col7\" >0.02%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow8_col0\" class=\"data row8 col0\" >9</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow8_col1\" class=\"data row8 col1\" >kotlin</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow8_col2\" class=\"data row8 col2\" >16574</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow8_col3\" class=\"data row8 col3\" >15000</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow8_col4\" class=\"data row8 col4\" >5475</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow8_col5\" class=\"data row8 col5\" >35542</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow8_col6\" class=\"data row8 col6\" >1274</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow8_col7\" class=\"data row8 col7\" >0.34%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow9_col0\" class=\"data row9 col0\" >10</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow9_col1\" class=\"data row9 col1\" >perl</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow9_col2\" class=\"data row9 col2\" >16309</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow9_col3\" class=\"data row9 col3\" >14000</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow9_col4\" class=\"data row9 col4\" >5000</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow9_col5\" class=\"data row9 col5\" >39992</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow9_col6\" class=\"data row9 col6\" >2343</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow9_col7\" class=\"data row9 col7\" >0.63%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow10_col0\" class=\"data row10 col0\" >11</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow10_col1\" class=\"data row10 col1\" >cpp</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow10_col2\" class=\"data row10 col2\" >15517</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow10_col3\" class=\"data row10 col3\" >13000</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow10_col4\" class=\"data row10 col4\" >3750</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow10_col5\" class=\"data row10 col5\" >37500</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow10_col6\" class=\"data row10 col6\" >62104</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow10_col7\" class=\"data row10 col7\" >16.58%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow11_col0\" class=\"data row11 col0\" >12</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow11_col1\" class=\"data row11 col1\" >swift</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow11_col2\" class=\"data row11 col2\" >15241</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow11_col3\" class=\"data row11 col3\" >12500</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow11_col4\" class=\"data row11 col4\" >5250</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow11_col5\" class=\"data row11 col5\" >36731</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow11_col6\" class=\"data row11 col6\" >3280</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow11_col7\" class=\"data row11 col7\" >0.88%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow12_col0\" class=\"data row12 col0\" >13</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow12_col1\" class=\"data row12 col1\" >julia</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow12_col2\" class=\"data row12 col2\" >15071</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow12_col3\" class=\"data row12 col3\" >15071</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow12_col4\" class=\"data row12 col4\" >12500</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow12_col5\" class=\"data row12 col5\" >21500</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow12_col6\" class=\"data row12 col6\" >7</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow12_col7\" class=\"data row12 col7\" >0.00%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow13_col0\" class=\"data row13 col0\" >14</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow13_col1\" class=\"data row13 col1\" >objective_c</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow13_col2\" class=\"data row13 col2\" >14661</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow13_col3\" class=\"data row13 col3\" >13000</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow13_col4\" class=\"data row13 col4\" >5075</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow13_col5\" class=\"data row13 col5\" >29750</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow13_col6\" class=\"data row13 col6\" >282</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow13_col7\" class=\"data row13 col7\" >0.08%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow14_col0\" class=\"data row14 col0\" >15</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow14_col1\" class=\"data row14 col1\" >php</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow14_col2\" class=\"data row14 col2\" >13625</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow14_col3\" class=\"data row14 col3\" >12000</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow14_col4\" class=\"data row14 col4\" >3750</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow14_col5\" class=\"data row14 col5\" >35000</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow14_col6\" class=\"data row14 col6\" >15772</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow14_col7\" class=\"data row14 col7\" >4.21%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow15_col0\" class=\"data row15 col0\" >16</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow15_col1\" class=\"data row15 col1\" >java</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow15_col2\" class=\"data row15 col2\" >13435</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow15_col3\" class=\"data row15 col3\" >12500</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow15_col4\" class=\"data row15 col4\" >3750</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow15_col5\" class=\"data row15 col5\" >31000</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow15_col6\" class=\"data row15 col6\" >125877</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow15_col7\" class=\"data row15 col7\" >33.60%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow16_col0\" class=\"data row16 col0\" >17</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow16_col1\" class=\"data row16 col1\" >javascript</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow16_col2\" class=\"data row16 col2\" >11916</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow16_col3\" class=\"data row16 col3\" >11500</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow16_col4\" class=\"data row16 col4\" >3750</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow16_col5\" class=\"data row16 col5\" >25000</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow16_col6\" class=\"data row16 col6\" >45734</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow16_col7\" class=\"data row16 col7\" >12.21%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow17_col0\" class=\"data row17 col0\" >18</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow17_col1\" class=\"data row17 col1\" >visual_basic</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow17_col2\" class=\"data row17 col2\" >11594</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow17_col3\" class=\"data row17 col3\" >11500</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow17_col4\" class=\"data row17 col4\" >4500</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow17_col5\" class=\"data row17 col5\" >21750</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow17_col6\" class=\"data row17 col6\" >40</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow17_col7\" class=\"data row17 col7\" >0.01%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow18_col0\" class=\"data row18 col0\" >19</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow18_col1\" class=\"data row18 col1\" >c_sharp</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow18_col2\" class=\"data row18 col2\" >11552</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow18_col3\" class=\"data row18 col3\" >10500</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow18_col4\" class=\"data row18 col4\" >3750</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow18_col5\" class=\"data row18 col5\" >27083</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow18_col6\" class=\"data row18 col6\" >47172</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow18_col7\" class=\"data row18 col7\" >12.59%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow19_col0\" class=\"data row19 col0\" >20</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow19_col1\" class=\"data row19 col1\" >delphi</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow19_col2\" class=\"data row19 col2\" >10452</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow19_col3\" class=\"data row19 col3\" >9000</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow19_col4\" class=\"data row19 col4\" >3750</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow19_col5\" class=\"data row19 col5\" >22500</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow19_col6\" class=\"data row19 col6\" >1263</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow19_col7\" class=\"data row19 col7\" >0.34%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow20_col0\" class=\"data row20 col0\" >21</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow20_col1\" class=\"data row20 col1\" >vba</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow20_col2\" class=\"data row20 col2\" >10348</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow20_col3\" class=\"data row20 col3\" >9000</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow20_col4\" class=\"data row20 col4\" >2919</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow20_col5\" class=\"data row20 col5\" >22500</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow20_col6\" class=\"data row20 col6\" >514</td>\n",
       "                        <td id=\"T_31dfa9f0_176d_11ea_aa00_701ce71031efrow20_col7\" class=\"data row20 col7\" >0.14%</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x235e473e348>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "apply_style(data_pl)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(21, 8)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_pl.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_pl=data_pl[['pl_','percentage']].sort_values(by='percentage', ascending=False)\n",
    "data_pl.reset_index(drop=True, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style><table id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031ef\" ><thead>    <tr>        <th class=\"col_heading level0 col0\" >rank</th>        <th class=\"col_heading level0 col1\" >pl_</th>        <th class=\"col_heading level0 col2\" >percentage</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                                <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow0_col0\" class=\"data row0 col0\" >1</td>\n",
       "                        <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow0_col1\" class=\"data row0 col1\" >java</td>\n",
       "                        <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow0_col2\" class=\"data row0 col2\" >33.60%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow1_col0\" class=\"data row1 col0\" >2</td>\n",
       "                        <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow1_col1\" class=\"data row1 col1\" >cpp</td>\n",
       "                        <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow1_col2\" class=\"data row1 col2\" >16.58%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow2_col0\" class=\"data row2 col0\" >3</td>\n",
       "                        <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow2_col1\" class=\"data row2 col1\" >c_sharp</td>\n",
       "                        <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow2_col2\" class=\"data row2 col2\" >12.59%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow3_col0\" class=\"data row3 col0\" >4</td>\n",
       "                        <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow3_col1\" class=\"data row3 col1\" >javascript</td>\n",
       "                        <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow3_col2\" class=\"data row3 col2\" >12.21%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow4_col0\" class=\"data row4 col0\" >5</td>\n",
       "                        <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow4_col1\" class=\"data row4 col1\" >python</td>\n",
       "                        <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow4_col2\" class=\"data row4 col2\" >7.96%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow5_col0\" class=\"data row5 col0\" >6</td>\n",
       "                        <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow5_col1\" class=\"data row5 col1\" >go</td>\n",
       "                        <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow5_col2\" class=\"data row5 col2\" >7.19%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow6_col0\" class=\"data row6 col0\" >7</td>\n",
       "                        <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow6_col1\" class=\"data row6 col1\" >php</td>\n",
       "                        <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow6_col2\" class=\"data row6 col2\" >4.21%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow7_col0\" class=\"data row7 col0\" >8</td>\n",
       "                        <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow7_col1\" class=\"data row7 col1\" >matlab</td>\n",
       "                        <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow7_col2\" class=\"data row7 col2\" >1.50%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow8_col0\" class=\"data row8 col0\" >9</td>\n",
       "                        <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow8_col1\" class=\"data row8 col1\" >swift</td>\n",
       "                        <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow8_col2\" class=\"data row8 col2\" >0.88%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow9_col0\" class=\"data row9 col0\" >10</td>\n",
       "                        <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow9_col1\" class=\"data row9 col1\" >lua</td>\n",
       "                        <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow9_col2\" class=\"data row9 col2\" >0.84%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow10_col0\" class=\"data row10 col0\" >11</td>\n",
       "                        <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow10_col1\" class=\"data row10 col1\" >perl</td>\n",
       "                        <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow10_col2\" class=\"data row10 col2\" >0.63%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow11_col0\" class=\"data row11 col0\" >12</td>\n",
       "                        <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow11_col1\" class=\"data row11 col1\" >typescript</td>\n",
       "                        <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow11_col2\" class=\"data row11 col2\" >0.48%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow12_col0\" class=\"data row12 col0\" >13</td>\n",
       "                        <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow12_col1\" class=\"data row12 col1\" >kotlin</td>\n",
       "                        <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow12_col2\" class=\"data row12 col2\" >0.34%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow13_col0\" class=\"data row13 col0\" >14</td>\n",
       "                        <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow13_col1\" class=\"data row13 col1\" >delphi</td>\n",
       "                        <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow13_col2\" class=\"data row13 col2\" >0.34%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow14_col0\" class=\"data row14 col0\" >15</td>\n",
       "                        <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow14_col1\" class=\"data row14 col1\" >ruby</td>\n",
       "                        <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow14_col2\" class=\"data row14 col2\" >0.30%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow15_col0\" class=\"data row15 col0\" >16</td>\n",
       "                        <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow15_col1\" class=\"data row15 col1\" >vba</td>\n",
       "                        <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow15_col2\" class=\"data row15 col2\" >0.14%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow16_col0\" class=\"data row16 col0\" >17</td>\n",
       "                        <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow16_col1\" class=\"data row16 col1\" >rust</td>\n",
       "                        <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow16_col2\" class=\"data row16 col2\" >0.12%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow17_col0\" class=\"data row17 col0\" >18</td>\n",
       "                        <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow17_col1\" class=\"data row17 col1\" >objective_c</td>\n",
       "                        <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow17_col2\" class=\"data row17 col2\" >0.08%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow18_col0\" class=\"data row18 col0\" >19</td>\n",
       "                        <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow18_col1\" class=\"data row18 col1\" >haskell</td>\n",
       "                        <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow18_col2\" class=\"data row18 col2\" >0.02%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow19_col0\" class=\"data row19 col0\" >20</td>\n",
       "                        <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow19_col1\" class=\"data row19 col1\" >visual_basic</td>\n",
       "                        <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow19_col2\" class=\"data row19 col2\" >0.01%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow20_col0\" class=\"data row20 col0\" >21</td>\n",
       "                        <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow20_col1\" class=\"data row20 col1\" >julia</td>\n",
       "                        <td id=\"T_31e3efd4_176d_11ea_b7b2_701ce71031efrow20_col2\" class=\"data row20 col2\" >0.00%</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x235ea929d88>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "data_pl['rank']=list(range(1,22))\n",
    "data_pl=data_pl[['rank','pl_','percentage']]\n",
    "#data_pl.style.format({\"percentage\":\"{:.2%}\"})\n",
    "data_pl.style.hide_index().format({\"percentage\":\"{:.2%}\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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gu4s/jwr8jNY2oAq/it/XGLy4rDHGGDPhWAEKY4wpIxH5Ln5J8J+q6t+KyM+AH6nqfwX73wpchx+cVAD34w+JuxQ/qIriD+sL4wckFfhV9UL4AUwWPzDSoE3ff/q/w89YNQT3PaAHf7jgUfxhf0p/IYnt+EHV/OD2smDfY/iV+R7Dn9v1ceCf8Yfz3Yof/EXw53UJfhn1k4CFqnpQRDpVtUZE5gC/xl8bTIHvjccCwMYYY8xYsmDKGGPGmYhU468LNR8/I/Mt4BxVfbWIXIlf5KEOP5DZh59p+nfgDuAy/EVtn8cPpJbgD9Wrwc/y/AH4B1W9LLjW/+AHWe/ALzqxA3g82NaEX/jhWfzg6Quq+tX8RXSDc1wPzAEWqOrlAx5LQdsB++YBdwFfVNUvFtn/FuBfgA+p6q2jeAqNMcaYCckW7TXGmPH3CmC3qq6DXLW+tmDf+fhZnfcA/wA8oqpHRHJVxe/BL2d+nareJiIX4QdRF6nq50VkAXCKiETxs1IvxQ+cFH8Y4Rn4Adxv8YfZ/VhV35DfOVW9aMD96/OuUzJV3Y1fbn2o/d8EvjmacxpjjDETmQVTxhgz/h4FPicin8FfMPdeEdkiIivxh8b9G/6cpS/iF4zIUdWvB4FNUaq6U0S+BzyCv1bVn4JdHvDV4Nrb8TNYO4IiFSNS1buAu0RkA/6CuvlW4S/EO2oi8o/AawdsvlVV/+VYzmeMMcaUkw3zM8aYEonI6cA8Vb0zuP9WYK2qvm+YY67Hn+/0f/hD9tqAnwe7O4F1wF/iF59w8YfQPSYiX8cPvG4bcPuioE3B8DtjjDHGnHhWzc8YY0p3On5ANFq1QLeqfhv4HP7Qu3vwK/c9oKr78eczrQA2jXCugRUAjTHGGFMmNszPGDOtiEgMf02l+4AX4K/Z9DX8CnSz8dd5AvgC/hyjHvx1n7YBnwAqReRFwA0DznsF8DH8ynUHgTeq6t5g9wuBAyISBnbjD3PbhF/k4Z6gzSPAPh15uMAj+GsxPQx8XVU/P7pnwBhjjDFjxYb5GWOmlSCY2gKswQ9o/oAfUL0DeCV+4PQW/ExSJljr6T2qetXAYX3590WkATisqioi1wIrVfXDwTC/V+EHbtX4c5rOCYo1GGOMMWYSs8yUMWY62qaqjwKIyCbgV0EQ9Ch+IYg64Bsi0reWUriEc84HbhGRufjZqW15+36sqj1Aj4j8Gr/oxI/G7NEYY4wxpixszpQxZjpK5d328u57+F8yfRL4taqeClyBX3J8JF8E/lNVVwHvHnDMwCEANiTAGGOMmQIsmDLGmMHqgF3B7bfmbR+u+EP+MdcM2HeliFSISBNwEf7QQmOMMcZMchZMGWPMYJ8FbhCR3+CXK+/za/wFcv8sIlcPOOZ64FYRuRc4MGDf74EE/sK5n7T5UsYYY8zUYAUojDHGGGOMMeYYWGbKGGOMMcYYY46BBVPGGGOMMcYYcwwsmDLGGGOMMcaYY2DBlDHGGGOMMcYcAwumjDHGGGOMMeYYhMrdAWOMMdPTc/F7w0AV/gLHFY+23+s+fvj+ilDVS51Q9LTwRXe/nw+/6tXpJ7wXhIFs8OPl3c4CnUD79vXrsmV6GMYYY6YxC6aMMcYcl+Zf/zkMNANzgeZ6bW/YwLUtQFPw09jePvfAY4++bC3+4sYzgJrz3ZV/Wp6dd3bfeeojs+4GLtTs4XuAC8BJHdWmXwOvGKkPsXiiA2gfxc8BYOf29et6x+RJMMYYMy1ZMGWMMWZYsXiiClgc/JwExIBFvWc2qTez4oXAHED62h+mvh1oyD9HRbTzAWBV/rZeMpn8+470rY/sKYCKKFDqYogzgp+FJbYH8GLxxC5g64CfZ4Ct29ev2z+KcxljjJmGLJgyxkwKIrIdWKuqB8rdlynr+rr5wCnAikT27Ma/Sn/wAuBkYB55wVIf6Uj/hpkVzUXOVJ/Fybh4ufcYN5SODmzUKxkv/76be0vq2ywe48sBFgQ/Fw7cGWS7tjE42Nq0ff26Z8e5b8YYYyYBC6aMMWa6ub4uip8lOh04DVgd3M9lk852nvwjcMZwp5HOTLr4DpGjWneogfbZ/ZsylQObdWV6wvn3k5neGQC92XTUnyQl6mUyFbgDjzxhZuA/N6sH7ojFE/uBh/J+Hty+ft3OE9s9Y4wx5WbBlDFmQhGRGPAz4HfAGuAp4C3B7veLyBVAGHitqj4hItcDS4AW/AzDZ1X1qye42xPWqm+scoFW4Ow/bnv2zDCcA5yK/xwOqYGOOSOdW4521wwYzZez80hdRUNde+5+V5d30sA2e47sXUFda+7+rqP7TgNoT3bFqmdAGokkO44uo36knpTFLPy5XLn5XHkB1oPB74cswDLGmKnNgiljzES0HHiHqv5GRP4PeG+w/YCqniEi7wU+AlwbbF8NvACoBv4kIglV3X3Cez0BrPrGqhnAucD5wHnA2fjPC09GIk+f2tu7rJTzuHjzKrQnmZTKiqHaeEePLPJj2MH2JWe41PXfj0R0UH4pI17BMD4HVwBcIQmAiOc4brKU/k4QxQKsffRnr34L3L19/brO8nTPGGPMWLNgyhgzEe1U1d8Et78NfCC4/YPg90PAq/Pa/1hVe4AeEfk1fgDxoxPS0zILgqcLgYuC32ug+MC4u6sq95YaTIkgi1NPpR6vOG3IYMrRiDNUPfIDmbqCQCka0UHvNxkpPNp1cgUoAFCk1OITE9ls4NLgByAdiyd+C/wi+PmDlXU3xpjJy4IpY8xENPBDdN/9VPA7S+H/X0O1n3I2r1jp4g/Vu+Rv3umezky5jBL/L7+XcP1fjeJaK9na8Tin1Q2135FQ9VD7DmdrCwpWuCEETXlINLdYfBavYOF4JxcD+i9fUM1vqgnjZw3PBz4BHI7FExsJgqvt69c9U87OGWOMGR0LpowxE9FCETlXVR8AXg/ch59xGcqVInID/nC2i4D4+HfxxNm8YuV84DLgEuAl4M8iOn+Td+/NF7ol/z++3QktGM11V7A9M9x+ccIV2ptOSyQ8aP7VYeoHV/+TnrQSzVX1yw4o1peXmRKYMpmpkdTjZ1lfDRCLJ7bRn7X61fb169qHOdYYY0yZWTBljJmINgPXiMhXgKeBLwPvH6b974EE/hpDn5wK86U2r1i5Crgy+DmTIqXJX7BZQzcPKug9tK4Z4RldBzVTLVLS//3L3d0j19E73NXF7PpBJSI6pHZwMEVPVvOqSWRFCzJTrvhzplT9daY8ZPCDnvpOAt4V/HixeOIh4KfArdvXr3usrD0zxhgziAVTxpiJyFPVtgHbYn03VPVB/AxUn6dU9V0noF/jZvOKlYI/fO81wKvwF8gdVv1h7wz1PMRxRmrqc8S5XyMHLpb07JEbw6JQ+6By5gPJ0Z6eYsFUt1s7qFOO9HheXq5JncJYyQkyU9KXmZJpGEoVcoCzgp9/isUTm4BbgJu3r1/3dFl7ZowxBrBgyhhjyiYIoM4DXos/zGv+aI6vUie6eKt3YNtSZ2apx9wbrui5OFt8eaiBmiM9ddrrITJ0sCYdqXSxsXg94bpBkZDjJJW8UgvqMDAz1ben7+zTYZjfaLTiz7P6RCye+CN+YHXL9vXrdpS3W8YYM31ZMGWMmVBUdTv+Okiltr9+3DozTjavWHkK8GbgjfhrYx2ztY9mO7ctDZUcTD1cGXXo7CipbdTV8LzM7o7nw/NnDNmoK+0V25yK1g3OTLmDgqmCgCsUjD7Uvmp+fgEKC6iKOyP4WR9UB7wF+N729eueL2+3jDFmerFgyhhjToANbRtnn/vAda+pTB16B/6H4DGx5lmit46i/a7qyAxGscrR8uyWzuGCKSfpFS2Pnq6oGzTfynUGLBnlFKa83NwwPxUAzzJTpRD8dcXOBf4tFk/cgx9Y3bZ9/boDZe2ZMcZMAxZMGWPMONnQttHFX1/oHcC6nQte/MDJW74/ZoEUQKzbmRVKeZlM1Cnp//NUpVu/35PkLEeHXD8q30qe6b2rYHpaIcnIoEp+ABqtclIZ14u62VzA5IZ6C48dGEz11cXQvsyUo5aXGhUHfy7hRcAXY/HEz/CLt/x0+/p19kwaY8w4KHHWsjHGmFJtaNt48oa2jeuBncDtwF8A4V1zXtA81tcKIaFTHs/uL/kAEe5xIiWX214uO4fd73jukEHZ/lRdQfQUCqUKhvWJ6xTNTOXWmSq1k6aYEHA5fpXLLbF44iOxeKKxzH0yxpgpxzJTxhgzBoIs1KuAD+AvyDqIhqtO3lUx52hLcm/tWF77rM3Z1CNriiaIivpNOJq6Kp0auSGwJLQ/Otx+kXDNUPv299al51cdygVboVC6cJFe13HIm3EVctwg2Mot2gtFSsKbUVsM/Ct+4YqbgQ3b1697qMx9MsaYKcGCKWOMOQ4b2jbWAG8HPoi/RtCwtrRcdKjlmVvGNJhavVuGDGiK2VQZDVNaQT/mRzpqKDYpKiCOG9auZFKqKwZlqPb11hcUpwiF04Wl0F1Xsr1Z7Vtfqq8ARd+cKcW15NTYqgTeBrwtFk/8DvgSfjXA0iJrY4wxg9gwP2OMOQYb2ja2bGjb+Bn8oXz/TgmBFEBqzpmzsmM8E2hO2mmqPprtKbX93prIoHWhhlIfytRUZjt7h210pKur2OZDmbqCYCoSyQx6z+nJ9uZCtf5hfn3rTAVRlRkP5wDfAJ6LxRPrY/HEonJ3yBhjJiMLpowxZhQ2tG08fUPbxm8B24C/A0oOTABCkerqZxpax7R8tYPI6Q9nD5baPht1q7d6Tkk1/URgaeaZo8O2OZpMFtt+yKsruB+OZAcHU5rM9N0O5Wpo9MWaDmpTp8bbTOCjwNZYPPGTWDxxSbk7ZIwxk4kN8zPGmBFsaNsowGXAh4CXHO/5drRcmD358Kbj7le+tU952d8UnalV3N1O9PBiekoaHrhCt/Q8ymlD7pfO3kyxiOeoFi7cG4l4g4KppJfKZaZC/QUo/NLoIpaZOnEc4ArgimBB4E9sX7/ux2XukzHGTHgWTBljzBA2tG2swF9c92+AlWN1XmlaPrfHqUhVeslhizuMxqkHnIbRtP9tJJp5W29pIwNXsGOYWVMg3RktFkx1OIUL90YrvEGxUY/XmxdMDZwzZetMlckZwI9i8cSfgE8AP7bS6sYYU5wN8zPGmAE2tG2s3tC2MQ7sAP6bMQykABwnFHp89tl7x/KcdZ5TO3t35kip7Z+sjpa0zhTAye7uYb94k6Q3aIFegC6ntjCYiuqg95wU6dy8qkGl0a2aX7mtAX4I/DEWT7wqFk/Ya2GMMQNYMGWMMYENbRujG9o2fhB4BrgBmD1e1zrQ8qIxy0r1WftItuRg6lBNuMErmk8aLBZurxxuv2QlUmx7MlxbEISFQgjamylo4/XmgilHHFQLMlP+L1NupwM/AP4UiyeusqDKGGP6WTBljJn2NrRtDG9o29gGbAE+D8wZ72uGZ7TM2R9tOjyW5zxja+n/p2vIiT6i4ZKuPyfSU6fqDbnf0VDRYCsVmTEoY+U4PQWVAVP0FgwhVBzIH+ZnodREchpwG/BwLJ54jQVVxhhjwZQxZhrb0LbR2dC28S3AE8CXgfkn8vpPzLtwTIOpk484M/G8ksOPu91IRyntIg6h+ZnnhmwrTrhGs4OnVWUqagcHU9JTkJlKaeGCV4qrIkFKSkQRG+Y3Aa0CbsUPql5rQZUxZjqzYMoYMy1taNt4KfAn/LV2FpejDz3NZzeWOtSuFBVIxZIt3oFS2z8YjQ6dbhpgeXbL0MGUOA4d3YOqWWi00klmQwVRluP0FNxPU1gIUPIzU+KA5aYmslXA94BHYvHEFeXujDHGlIMFU8aYaWVD28YzN7Rt/BVwJ7C6nH0JRWfUbqs7ec9YnnPtY9miC+gW80x1tKrUtivZmh5uvxzuKloacH9vfcF210kWBHC9OrCquqP9c6ZQsQIUk8GpwE9i8cQvYvHEqnJ3xhhjTiQLpowx08KGto0nbWjb+F3gD4zBWlFjZXvLRb0jtyrdmmcpuUpfR024MekNMxkqz3LZOcLJUqlim/f31hc8PtdJFgRPvWQKD9D8OVP2FjXJvAy/SMV/xeKJWeXujDHGnAj2TmWMmdI2tG2s2tC28Qb8eVGvZ4JlOnRma3NKwsNmfU1uI6oAACAASURBVEZjYY8zK5z0MiO3BBxxfy/hQ6U0XRLaP2z1QenKFA0K96frC4b1uW5hzJWRgXOtXPqyUUFpdBvmN7m4wLuBp2PxxN/G4omilR6NMWaqsGDKGDNlbWjbuA7YBMSBCfmhznHDkc2z1j4/VucLIe6pm7L7Sm1/T6iipGGB8yMdNcPtl55s0aDnYKahYLsbGhBMURhMKaK2aO+UUAd8FtgUiycuK3dnjDFmvFgwZYyZcja0bWzZ0Lbx+8AdQKzM3RnR3pbzxzTQO3NztuRM15+i0ZIydXXhbE1VtmPIIYnSq0UX9j3k1RUERKFQquB6GfEK7vsFKILsoVhp9ClgKZCIxRM/jsUTsXJ3xhhjxpoFU8aYKWND20Z3Q9vGv1HVJ4BXl7s/pQrVLmxuj9QfHavzrd4jw2aR8u2siZTcdllmy5CLAjtZp+gwwCNaX/A+EwqlC+5nBwVTLhJEVP4wP51QwzLNMXsl8HgsnvinWDxR8rw+Y4yZ6CyYMsZMCRvaNp6tqg8C/yZSejAxEYgIm+eeX9LcpVLMSTtNM9qz3aW07akKNRzxKKkIxkpvS3KofUKoaGXADilcayoUHhhMFQZLIi42zG/KqgT+GX/o37pyd8YYY8aCBVPGmEltQ9vGug1tG7+kqg+IyOnl7s+x6pj7gvqxOpcgrHkke7C0xiL3SqSkQG657Bi8Mm/faZxwtabTg4KfLrcwmAqHMwXvOyo64H3IUfoKUOBYZfSpaTFwRyye+HYsnmgod2eMMeZ4WDBljJm0NrRtfH0wpO89IjKp/z8LV9TXb685qeTCESNZ+7RXclbnN+GKITNO+U52ny86Lwr87Jq0dwwqj54MzSg4JhzJFARXnlP4PiQ4+dX8LDM1tb0ReCwWT1xa7o4YY8yxGvKN0RhjJqoNbRuXAl8CLhaZOpmLrS0X9sSe3DYm5zrloFPyN/6PVEZDdIzcLhZuH36R3yNdvcxuLJgP0xstDKYiEa8gmGJgMCV5c6ZsmN90MA+4MxZP/C/woe3r143Z3EFjjDkRJvU3ucaY6WVD20bZ0Lbxfar6CHBxufsz1rKzVjf3ilvaGlEjqPWcGc27ModLaft8TaS2lHazI8latHgJdAA5mhxURTBbURPOvx+JDgympOC+n5kK5kxJEFOZ6eAdwKOxeOKl5e6IMcaMhgVTxphJYUPbxnmq+lPgiyJSWe7+jAc3FI0+2bRmzNacOvOR7JDV9/KlK9za3SojFqwIO4QWZHYOncPqzgwKpjQcdboykdz2SFQHBlPFhvn1VfNTmzQ1rSwEfhGLJzbE4onqcnfGGGNKYcGUMWbC29C28TWq+piIXFLuvoy351sucEduVZoztxZf+6mYuyRaUhZreXZL51D7nJQWX7i3t76n77brItCbC67EcQozU36iqq+an6Wlph8B3gs8HIsnzi93Z4wxZiQWTBljJqwNbRtrv/juX34LuFVEpkXVL7f+pLlHQzVdY3GuZUfdmZItrRDFA5FoaeXR2TrkgsCSLj6BbV+moaAwhSvJ3H1xC4MpJ2+dKb8uoZmmlgB3xeKJz8fiiSmZiTbGTA0WTBljJqQbr7783K7Dt3zPEedN5e7LiSTiyOPNLzowFueKItGlT3slnWtzZTRSSrvl8tyQ+0TDRc9xMFNfEKi5Tk/uvuM4blb7K67760zlL9prpjEH+CDwp1g88YJyd8YYY4qxYMoYM6HcePXlzr++bt3HVPVeV3ddcqj9vr3l7tOJdmTeuWO26PDaxzIlZbn210RKyvwtDu+vGGqfI+Gi1f4OZBu9/Puu21+oQkToyfbmsmcOjuaCKURtnJ8BlgP3xeKJeCyesAjbGDOhWDBljJkwbrz68nlZT+92RD4pweSZiPe7umRqfwmFu6eOcNXMpueqWsYkO7VmZ2nFOryIU7nZc0csSz0/3DlkoCdOqEJ7kt7A7Ye8wvWIXTdZsPhvt9eTO8YRR0QEz/MsM2XyucANwA9j8URduTtjjDF9LJgyxkwIn3vduss91cddR16Uvz3kSEX3kVu6PK/0RWingi0tLx6TeVMLks7MSI835DynfPc4kRGr/9WGs9U12SODFuftI4eODrrWEeoL3mtCA4OpbKo/MyV+zQwl66k40+o1NyW5EngwFk+sKndHjDEGLJgyxpTZjVdfLp95zaXrgZ84IkW/ca4K9zYfOvSTHSe4a2WVnr1mdgYZlOUZLRdxWzdl9pfS9vfRipKutyy7Zeig63DnoGDqKHUFRSbcULIgSOrx8oMp/21JdZpFz2Y0lgK/jcUT02o+pTFmYrJgyhhTNjdefXltbyb7i5DrflRk+DFdVc4zCzu7nh6ToW+TgRuuqHyqcfWYrDl19mYtKTP1VHVkyPlQ+VZ6zwydmepMZQdu63ZnFJRoD7mpgtc6qalcECf4cZeS9dRfc8qYYqqAb8XiiS/F4omSiqcYY8x4sGDKGFMWN1z1ilPS2eymSMh9aSntHREn231HKJPtKSkwmAp2tVw4JsmZVXsoqaDFkZpIY1qLrxWVbwXbh8xgSXdm0L5kqKbgw24oNCCY8voLULi5zFRWbc6UKcF7gHti8cSCcnfEGDM9WTBljDnhPv7Ki//SdZyHwq47fzTHRUNaf/jgzWOSrZkMpGHp3E63smfklsObnXGbatuz3SO1U1fCf9Rw+0jtlrl7hlxYWHoHB2O94YHBVLrgvSel6bxhfkFmSj0PRBWr52dGdA7wx1g8cXG5O2KMmX4smDLGnDA3Xn25XH/lxf8+oyJyk+s4JQ0pG6gm3L6w/fD9Qy92NIU4jus+PueF+8biXGc8nD1YSrt73GjnSG0Whdurh9onGXdQOilbUVUYTIXTBcP+8oMpt68ARZCZErWRfqYkM4GfxeKJj1n5dGPMiWTBlDHmhPj0q18xozvVe/eMiugHRpgeNaJw9oGZydSBET/0TwXt884runbTaJ35dGm1LB6qiI7YZnYkVSuaLZoxEsLhQRtDEaczU5FbqDcUThdktnrpH7nZV4ACPE/F3qLMqDjAJ4GfxOKJ+pEaG2PMWLB3KmPMuPvnKy8+BeGJqmjk/LE4n18u/ebO6VAuPVwzZ9aeijmHjvc8pxx0SlqUd3t1dMTgLeTgLszsKLomleNEi2Yc9/fWJ/tuh8PZgsxUr2byMlO5YX6qyJR/fc24uBy/2l+s3B0xxkx9FkwZY8bVP73yZa+pjIQfioZC88byvNOpXPqTLReOuJjuSGaoUzPv2cyI86G6qkONXaqZkdotz24pug6WOKGQHu0YVNFvf7o+VwEwNCCYSkt/81wwRVY53hSmmc6WAw/E4okzyt0RY8zUZsGUMWbc/OPlL/m7GRXRW451ftRIpku59NSctTOzevyFGM58NDtyUOaIc79GRsyErdStQ1ZVlINHBwVTB7KNuWF+4YhXMBQwnRe7uY4/58pfZ8reosxxaQbujsUTl5S7I8aYqcveqYwxY661pVn+ft2Lv9JYXfUZR8Zv4kt/ufTklC6XHopU1zzTcMpxVzE8cxuhkVvBfeGKESsILnd2DblPjnQNCqYOZhty2yIRLQimMnlrEzvBOlMeWavkZ8ZCDXBHLJ64ptwdMcZMTRZMGWPG1CWnnhy54rSVP5tZU/2uE3E9v1z6TbtPxLXK6dmWCwcFKKO1pMOZKRlvxEoUD1dGR3xvWBzeP2S2UTqTg/raro395c9dREjlAuCs9M99CzlBbQr11ApQmDESAr4eiyc+Vu6OGGOmHnunMsaMmctWr5h15qL5D86aUf3yE3ndmnD7oilfLr1pxdweJ5oaueHQokh02VPZ/SO1e646MmOkNi2RriHbSHJwpb/DUlhczZFk7rFk8zJT/QUosoo/ZcqyU2asfDIWT/xXLJ4Ycp00Y4wZLQumjDFj4qozVy1du2j+Q001VavKcf2pXi7dcUKhzbPP2XO85zlrU3bEIXypSrd+vyfJ4drMCGWrajPtxdv0Dq4b0SF1Be83rpvMzaHyHM0dEMorQKGICrbOlBlT7wZ+GIsnxmTJAWOMsWDKmAlMRK4TkSdE5BcicpOIfERETheR34rIIyLyQxEpqeT1eHrDOWvOWr1g7gN1VRULytWH6VAuff+88467kMfpz0nliI1EuEciI1b+W5Z9pnh5dC80KADqcmsL5mu5Tk+u6oRKf8DkBAUo/GF+Vs3PjIsrgI2xeGJmuTtijJn8LJgyZoISkbXAVcAa4NXA2mDXN4GPqupq4FHg4+Xpoe8tLzzz0taW2RtropGyfzDxy6Xf/my5+zFewrXz5xyINB05nnPMTzqzol1e70jt7o9ER2yzwttSdNihSHTQwr2pUE3BasCum+wPpvLeifoyUx6eB6JTNjI25XYOcH8snlhc7o4YYyY3C6aMmbheBPxYVXtUtQO4HagG6lX17qDNN4ALytXBt59/1ttPmTv7hxXhcE25+jBQlbNlQWf31C2XvrnlwhEzRsNxEWfVpsyI86Y2VUZHrPy3UnYULWYhbkWEbGENinS4qiCrFg71F6lQpz8z1V+AIositmyvGU/L8NeiOrPcHTHGTF4WTBkzcU3YIU6tLc3y1vPWfnhF86yvhENudOQjThxHxMl23eFO1XLpPc1nN3rHma85a7M34qK8e2sidSO1WebuKRpwiTjCkY6CzFY2UhhMuW4qF4iJ21+2LyTBOlN4fQUojBlPs4Ff2uK+xphjZcGUMRPXfcAVIlIhIjXAOqALaBeR84M2bwbuHuoE46G1pdk5fcHc606ZN3u96zglrVt0okVD2jBVy6WHojNqt9WdfFyFKE7d59SO1CYTdWu2qTNsQY9FkcNDTuKXQ0cKAzbXdY6kq3LDAsOh/hGC4ji5qKmvmh+atdLo5kSpB34RiydOL3dHjDGTj71TGTNBqeofgJ8ADwM/AB4EjgDXAP8qIo8ApwOfOFF9am1pDrfOm/3p1QvmXjdRA6k+U7lc+vaWi0aczzScWRmnof5AdsTKh3dJ9PCw5wmn6hxNFx/qd6R7UPrsQG9drpJgKNz/EMR1cu9FYaevNLqnaoP8zInTiJ+hWl3ujhhjJhcLpoyZ2D6nqsuBvwCWAw+p6p9V9QWqulpV/0JVj2sOTalaW5orlzfP+tyZsfkfDk3wQKrPVC2XrjNbm1MSPq5hjGc8kh3x383vItFhFwp2HZxFmR1FK/pJ1+DaFPsyDbkIKhzur5/u5AVTISfUN8wPrJqfObGagF/F4omyLO9gjJmcLJgyZmL7bxH5M/BH4Puq+sdydKK1pbl66eymL5xz0oL3TJZACnLl0js8r2jyZNJy3HBk86y1xzXU78wtI5eQf7IqGhmpzfLslq6iO3oyg95fDmYbcgFgKJzO7XdcN3c7N33Kz0yNdHljxtpM/ICqtdwdMcZMDhZMGTOBqeobVPV0VV2hqjeUow+tLc3VS2Y13fjCJYveFnKdQSWvJ7qqcO/cQ4du317ufoy1vS3nH1dQu/KQ0zRSm4M14RGLXaxkW9EMmaQHv70czDbmMl3hcDrXfxGhO5tUgHAQq+ct2mvMiTYLP6BaWe6OGGMmPgumjDFD8gOpxs+dt3TR2ydjINWnytmycKqVSw/VLmhuD9d3HOvxNepUz9+ROTRcGw070Uc1NOxwwOXOc0XfR0TDg+Kgdm3IpQhD4WxBMNjj+dX9Qo6LqqLqKX6WyuZNmXKYg7+w7/Jyd8QYM7FZMGWMKaq1pblq8azGz072QAqmZrl0EUc2zz3/4PGcY+0j2RGDsXvc6LBzzhaHDlQU2y5O5aDM2RFp6F9PKpwt+DfVnU32l0rHzYKHimCxlCmjZvyAalm5O2KMmbgsmDLGDJIXSF0bct0R581MBn659JufL3c/xlLHvBfUH8/xa7Yz4lDB30crhp1wNi/SNaPYdnErQqQLK/11SF1/oYmwV/DvqsfrzYuanKxqFhB0Aq+3ZqaFecCvY/HEknJ3xBgzMVkwZYwp0NrSXDm/ofZT5y1ddG14igRSfWrChxYePvzAlCmXHq6or99RE9t3rMcv6XRmOenhq3NsrY5UDre/JuRV1qUPDCrdJyJI+5Fk/rauUG0ueAuFtWCx56TX25+ZEtcDT4NyfpaaMuXWgh9QLS53R4wxE48FU8aYnNaW5sqmmqqPXXDy4neFXTc68hGTTyj7QFNqCpVLf6blop6RWxUXQSInP5ndP1ybo9XhxqSnwwZcy7JPF63o5xzuKFi4NxWqyQXnjoMjpHLDLnu0PzMlOF7/MD9jJoQF+OtQzS53R4wxE4sFU8YYwA+kaqKRv33pyiXvqQiHqsvdn/EScqjsmkLl0rOzVs9J4w67HtRwzt7kJYdt4EroDxIetlDFSm9rd7HtAxfuTYerC+ZXOZLMZbRSmj+dzc3aor1mAjoJuD0WTwybrTXGTC8WTBljaG1proi47gcvbl323ppotKHc/RlvVeHeue1TpFy6G4pWPDFzzTHPBTttFyN+MLzHrSgaLPVZ6T5bNJiTrt6C+14kWnAt103mGqTy5kw5/jA/EMHSU2aCORv4TiyesM9PxhjAgiljpr3WluawCO99eeuytoaqyjnl7s+JUulsWdDZvWVKlEt/vuWCY/6/fF7KmVnR5Q2a85TvTxXDj/hc6u4tXsgi6RX2y3Gd9t7qXCbMdXpywwBT9I8IFFwP9bBFe80E9Srgc+XuhDFmYrBgyphprLWl2QGuefHyJdfOrq1ZWO7+nEiOiJvtun1KlEt360+aezRUU3Te0ojHIs7qRzPDBpXP1kRqhtu/KHy4+LDQjOMO3LQ/XZ+b4+W6yVwE1Zs3zE9wPcUDxMIpM1H9TSyeeF+5O2GMKT8LpoyZplpbmgV4zdknzX9XbGbDynL3pxymSrl0EUceb37RMWfZ1j7hZYbb31MVajjiMWTQOTPSW+t6qUHzm0TDgzJWB9INufOEQ8nc8MC0ZPsLUPRV8xMb4mcmtC/E4onLy90JY0x5WTBlzPR18cq5s9/bOm/O2nJ3pJymSrn0I/POHTZ7NJxV+5y6YRuIyH0SGbIIhSs4C3u3DaoqWGzh3gPZxlww5bqpXBWQtGZygZPgeuCJioNVRjcTmAvcHIsnzih3R4wx5WPBlDHTUGtL8zkLGuv++uyT5p8n9u3/lCiXHq6a2fRcVcsxZaeask59w/5sx3Bt7gtXDFv1b1l2y+C1pkIVDj3JgioUB72GXBYsHOo/JCP9NSwccUE9BbE1e81EVw3cEYsnptUwaWNMPwumjJlmWlualzdUVX74ouWLL3Idp3jhgGkm5FDZeeSWSV8ufUvLRcc0bwrgzIcz7cPtf7QyOmj+U74V7Ogttt09crQgY9WujblUUyjcf0hW+p/7YJgfigX6ZlKYCyRi8URtuTtijDnxLJgyZhppbWluCbvOh192ytILwq5bVe7+TCTV4dTcQ5O8XHp69ppZGeSYIsIznxk+BbS7JjLsB8Xl7q6i13UOdxbMtToi9bnrhMO9udsZ+g93cBUUi6XMJHIqcFssnrAvqIyZZiyYMmaaaG1prgc+9NKVS180oyI6bUqgj0bVJC+X7oYrq55uXHVMBTVWtEuTDpOZS1e4tc+rDLne1LLIwaIfIuVo4cK9HU5dLsMVCqdz70Geo/1zpsT1UE8UUdQmTZlJ42Lgv8rdCWPMiWXBlDHTQGtLcyXwgbWxlrPn1ddOy8p9pZgK5dKfa7nwmIKPanWqFm73hiwyAXAX0cND7WuJdM0otl260gXppW53Ri7oCofTudue9AdTDq6qv2ivYJOmzOTyjlg88Tfl7oQx5sSxYMqYKa61pdkF3rGoqf6sU1uazy13fya6yV4uXRqWze1yKgdV1ivFWY9ljw63/4FItOi8KIDqkFdRn947qMS6pLyCuVap8IxI3+1QOJsLpjTv3ciREIJicZSZpD4TiydeUO5OGGNODFG1ERTGTGWtLc1XzKiIvunK00+5NBJyi2YPzGBJOfe5+vpz55e7H8dixlPf33HW7o2LRnvck9XZ3dd9IDpvqP1zDiV3//LIviH3X3XwPd0PVZ+fm4vXs/UhDv3iS57nZh1NZ5BwCO3pVnq6Jf+tJxqNks1mmVXZyKHuw6SyA2I2N4RTVY/X0T8CU6obCdfNQlVJ79lCuKWVuW/4tC1NZSaKncCa7evXHSx3R4wx48smShozhbW2NK92RF57SeuyF1ggNTp+ufRlndHozGNev6lcDs07r4rdG0d93OIuZ5ab9rLZsFO0ct/+mkj9zx7K8Nc/S5L1lGvPiHB6s5u7P29ZQnoWVXHgzi/g9RwFVcJNLeId3AWug2YyMES66fRVp2Ufe/QxN2+KlAoCjoN6nnhd7SAuCDgVNXg9R/GiVWS7D+M2zKPx/DdYIGUmkgXAN2PxxOXb16+zb62NmcJsmJ8xU1RrS3Mz8FcvXbmktbaywtZAGaXJXC49XNM8a2/FnGFLnRc9DgmveCJ7AKDjkQ6eij/FU3/3FPvv2A9ANiRV1yaS3k/fWMXP3lTFp+5J8cqbuhHgxksqeGbLM5H9t38OL9lJqG4OuCHCsxcjjU0QjkBtHVT6iavqaqG2VhQgnU7zxNNPurNrmjg/5q8h7YqoIERnNPSiHnhZPwxTRcUB9cj2HEVTPURmxahYuGpMnjtjxtBlwEfL3QljzPiyYMqYKSgoOPH+0xbMXbygsf6McvdnsprM5dKfnHfhkWM5bu0mr0c9Zfe3dhP7UIyln17Kkd8dIbkrSc/WHqrr3d7FDQ6f/U0vZ8x1WFQv/ODqSv76p0nWzA1ltLebuhf+JVUrzseJVJFp3yOkkuo2zkSUXLnzigqhp8cvOuF5Hp2dnTx/dB8PPfcYAFlVR1Hx0r3B+5QfQKEe2tUOoSja20No5kIaLnjzGDxjxoyLT8XiifPL3QljzPixYMqYKaa1pdkB3jKvvvaUNQvmXlTu/kx2k7VcerJ57UxvhLLi93Z1ctnWrVyy9Rm+etCf2nHaLqp7tvYQnRMFB3bcuIPM0Qw7Pr+Dnp09ZOsjmScPZPnh5jQPPe+RzsKRpDK3RnhoR1cET8m076bz0V/gJTtJd+xHu7oke6Qd7TwKSb82Rnu7RzoNjiOEQiGqq6upCEWZWdPY1z2dVTO7d+biVUdBIFpFqG4O0YWrkao6PybLZsgc2sXur7ax4zNXsOc7cbJdo07IGTOeXODmWDwxq9wdMcaMDwumjJl6XhoNuRdetHzxhY7j2LzI4zRZy6WHItU1WxpOGbIqYVaVT+3dy1fmz+f2kxZzZ8dRtqRSzOt1ZsruVG+4Mcyem/dQf149c143h4oFFRx54AgdYcf9ykNpvnhZBWEHnj2iXPbdbl60MMQpMwVCIbq3/A63qh53RhPa1U5o3qLeihdfglTX5DJTkaiwcGEIz1M8zyMSieCpsmrOybk+ZryM7HniDw2gkOqk6fKPkD6wA3HCaG8PuCFAkXAFbu0sevdt5ehDt4/7c2vMKM0DvhOLJ+wzlzFTkP1hGzOFtLY0rwDe+JKVS1srwqGGcvdnqgjKpe8udz9G69mWC7ND7Xs0mWRhOMKCSISICJfOqGVjZycOIgu2ZTsBUrtT1Jzi198INYTo2d5Dd5dX4Trw82cyLKoTqiNwy1WVfPnBXpY2IK4jNL7kWuZe83m87qNIqILMoX1u6pd3or0pyPpdSiWVffv6K6mHQiGqIlEW1bf0bZLDPe0hN1KRxQmDEyLTvhs8Dy/VAU4IJ1IBnqLq+XOpNIumU+P0bBpzXC4GPlbuThhjxp4FU8ZMEa0tzTOB953aMqdxbt2M1eXuz1RTEz606PDhB54rdz9G8u27/pX4N67iX773DmhaMbfHiRZEF7/v7uLsp5/iI7t38Viyhy8d8Ecw1jjCd9oP8cptW6nZmpL0oTQVCyvYfuN2UrtTeD0e2qsk96Zk6ZLokVsey/DUIaUqBLdsyjAjCvfu9HBFtXvL71Avi3oZNJ2E3pSjjgNO/1uOKiST/m3P89i/fz8Hug7zhfu/nmvjqSfp7qNhvDTRRas59PMv4aVTkE6B4yCRKsCDTIpsx37caDUz1lw27s+xMcfo47F44iXl7oQxZmzZOlPGTAGtLc1R4KN1lRVLrjx95WtDrltZ7j5NRRmPnnDNW7ITuVz6lt2PEA1X8M1ff4Z/fN3/Uv/ELTvO2HNPbs2p33d38bVDh7iyro7fdHXxyea5AHx09272ZtJsmD+fa3buzD49I+s2vriR9nvaSR9MU7u2lq4nupj7+rl03bQ709ORDV26NMSly1zem0iR8WD1HIfDzMju2N/l4mWRcAUVi1bTs/VBpKEJqavD27WTaH1Nen7N0bDrKtu2edTXN3L55Zdzfs9y3v/9f6a+qjb94lUrDlfJKu+bD9/U4FXWR2a+8u8IN7YM+biNmST2AqdvX79uT7k7YowZGzafwphJrrWlWYDXASe9ZOWS8yyQGj9BufTnwzPfU+M4EzOxv3Teag529H9O2z/vvAr23DOoXXMozJ50/zC7Ts+j0nHo9ZQKEXfZK2Z1b77l+Sq31mXWFbNoenkTT37wSSQsvPyjC3Zd9+z+Re+8PclHfp5iSYNw+lyXa06L8JTO6fn7P86uyXYfYc7rPom4IZLb7us8+IfbanBDNPz3zcyr7Nz7+aZ/mg/w6ENLDx3uOrcRYMGBefrEh/6f/PnQpt2/P/CrUK27InvGq9//7K45a5eO+xNnzIkxB7gpFk+8bPv6dUMOwzXGTB4T89OAMWY0VgEXn7tkYXNDVeWScndmqvPLpd+xo9z9KFW4dv6cA5GmgjLpf+7p4fo9e3iwp5v7OjvpVWVnupdOz+Ndzz3HXzXNpOnRVKr5dc0s/+xyZr9yNgfuOEDTy5uoXVPLtupo9SmzXD79kihvXxNh8/tm0Fzt4Agsjh52NJuh+fU3IK7/fV3FgjWhpv+9laavfJfQgkV0h2aE+/oSCqVywyO61R+R3GR9jwAAIABJREFU6IoroJKrVmHM1HIR8Dfl7oQxZmxYMGXMJNba0lwPvHtu3YzM8jkzX1bu/kwXVc7T8ydTufTN8y7I1Qs/JVrBL5cs5UcnncS1jY28d9dzXLFtK5fV1vKthYu4oKaag9kMB7Z2VzmVDpv/ajOb3r2J5HNJZl3hV3fuqg41dme97KfuTXHdBVEA3nVmmPgvk3z0jgNVtWe/urADbmWUbDYXNKVCNZG+26FQb2570usFwCEIpkRg+OruxkxWn4jFE8vK3QljzPGzYMqYSSpYT+oaVyRywcknXWpl0E+cyVYuvWfu2Y1eMD+2xnWpDoYo/tXMWcwOhbh54SLammYC8P6Zs3gsmeSv65rU6/Vofm0zK76wAi/p4YT71s8V534neugXb66modJPHq2c5fLHd9ew6b01zJvTWPi8iCPS0dXZdzcTqaroux0Op3PZp75gyhVXBBVFsNSUmaIqgf+NxRP2T9yYSc6CKWMmr/OBMy9asXhldTTSXO7OTDeTqVx6KFpbu73u5D0A+zMZ+goPPdLTgwfUu26u7fbeXvZlMlxQVVNRvyvT1fcu4aW9gnPeF6roHup6S9JPDQoy3SMdPX23NRypyHj+Z8hwpL9pSoPMlDiAgtgwPzOlnQ+8r1wXF5H7y3VtY6YSC6aMmYRaW5rnAm9aOrvJWdhY/8Jy92e68sul/3ZXufuR72u//BQ3/uj97D2yk499+2ruf+JO7n38dv6vRyIAP+/o4JXbt/Gq7dv49L693DhvXkHM8u8H9vOBmf5wvstCNQfb72tn6ye3MvMVMwuu8+fK6JDvH0uyWweNzXOO9vSXaBdHDiRrMwDhSCZ3npT6BTFccUVEHSwvZaa+G2LxRKwcF1ZVe+8wZgzYsCBjJpnWluYw8M5oKKTnnLRgndi392UVytzfmOpd1hWNNFWXuy8Ab3tZ8XVBs9nemtR9f5t+Y0ND+I0NQ6/n/Pl5/eXHL9gXCv+/jxWvafJcdaSGzqK7WMquQYGW05kqqFy2t6cu01x1JBSOZHNpsV78LJUrriN+AYoh+2nMFFEN/A9wwue8ikgn0Az8GGgAwsDHVPXHIvIZYIeqfiloez3QAXylWPsT3XdjJhLLTBkz+VwGLL7g5JNWRcOh+nJ3ZroLuVR2Hr75qOd5IzcuwvOyrL/t3Xz5p/8waN+vHrmVT93yNj5967X8x+0f4VDHXgD2Ht7JZ77fxg23vpOtezYBkPWyfPGOv6U3nSx6HdeNRDbPWvv8aPoW63Jmub1e0fLNqUq34aCSKrZvaWjfoG2SzBZERgfT9VmASH4wpf6lXHH8tvZFgZkeXhqLJ95ZpmsngVep6hnAi4Ebgy/obgauzmv3OuDWYdobM21ZMGXMJNLa0rwUeNXCxvr0/Ibac8rdH+M7nnLpv37sB8xpWFh034Kmpfzdq7/MP7z2f1iz+AJ+9Nv/BuC+x2/nledcyzte/nF+9citANz7+E84a9nLiIQrip4LYO+888ND7iwijIROeTw7ODICkP/P3p1Ht3We56J/vm/vjRkE53mASFHzLFGSTcmz5NiyLDtJMzpOHMdxbKe3OR1OtNqedc5tzkrT256m073taU4ztGmbNHMaNq4dp0kcO/U82xptUjNFijOJaWN/9w+QEEGAJDgAmyCf31pZBTY2gJeJWPDB9+73E/g5nP2ZHlrtGtTSDkZFSidEr5kIU4bDStZkIhGmpJBCYLzNj8P8aGX4k+DRjnob3lcA+LwQ4lUAPwFQB6BKKfUSgEohRK0QYiuAfqXUmenOt6FuoiWDYYqoQGysq/YAeFAAA3ubG27jt4FLy3zGpfeP9OCNrmdw7brbMz6+pm57MhwFq9ZjYLQHAKBJHTEziqgZgSY1jEVG8HrXr7BnzcEZ308PNFb3G4HhudS46814xtUnAHjacGZcBqtxRR2GFU5dqounbibdb5VYAKA71NUwJSbClJb4bOK/cFo5ipBoocu3DwOoALBTKbUNQDeAiW9kvg3gvUisUH0ji/OJViSGKaLC8T4ApXtbGlt9LmfdrGdTXl0dlx4xs33Od57+f3HX3k9m1c32q2M/xobG3QCA6zYewU9f/Ta+8Ysv4tbtH8KPX/h73Lr9w7O+jhBSvFVzXV+29QHA1oti2mvBXvc4M650aQIImqdCk48pOD2T7w+gWAGAlBDKClkAYApr/PlSJlamJJioaAW5PXi04948v2cAwGWlVEwIcSOApkmPfQPAB5AIVN/O4nyiFYlhiqgAbKyrXgfgxhKPe7C1qvxmu+uhzMbHpWc13e+1rl/B7y5BY8WaWc999sTjONNzAjdvfR8AoNRfhc/c+af47bv/Cg7dhcGxK6gqbsDXfvqH+PLjn0P3wNlpX2u4dm8gyx8HAFAdleWeoXgo02PdPse0r9USO50aKqXThWgseWxYXH2qwJgFAJZI9PQlBlBAQAgh2OdHK8ufBY925GurCwXgHwHsEkI8j8Sq07Hkg0q9AcAP4LxSauJ6y2nPJ1qpOM2PaInbWFftBHAfgP59rcGDupROu2ui6fmMK00DA/95vrh474yrh29fegOvdT2NN848g1g8inBsDF974vP46M2pgyiOnXsB//7SP+Ezd/4pDM2R9jr/+uyXccfu+/Cz17+HttU3o9RfjR+/8A/42M3pAy0AwHAVF3f5gpebRjors/l5JITY9mr8ytP7tLTrOUyn5nvbkmPN0vJMfaxVdeHRyQeEgBwaHrXKSwMAMKIXJZecBEKWAhAfX5mSQkoIxRhFK1EJgL8GcHcu30QIUQagTynVC+Ca6c5TSm2ecn/G84lWIq5MES19BwBUbqitLKvwezfaXQzNLjEu/croTOcc2fMJ/M97vok/+PA/4b5bfh9rarelBamzvSfxjSe/iAff9Tn43enjzE9eeAUBbxkqA/WImREIISGlRNTMPNFvwum6GzKuNE2n7cT0owp/ITMPoWiRF9OGUGiDI8n3DRmB5OePlCEFAGr8SKLND0KA1wXSinRX8GjHkVy9uBCiFsCvAPxJrt6DaCVhmCJawsY3573boWmXtzXUHrK7HsrOQsal/+i5r+DVzqcBAN//z79FJBbC3z3+B/jDb38Sf/Po1T2klFJ49MWv47adHwEAtK8/hB88+yX8n8f+R7IdcDrxii1VMWgZR55nsrFHTtvO94zDGct0vNnoS7ueSg6HoxO3I46iZNiSIjGsYkqYksxStIL9afBoR066EJRSF5RSa5RSf5mL1ydaadjmR7REbayrlgDuARDdvyZ4jcvQp99plZYcrxGp6ev/UVd52Z2zXqC9pnYb1tRuAwDc0XZf8viv3/HH0z5HCJHyeHVJE46+J7thYJrudB0r33Zuc+8LWY1iLrZkoOKCOdxTq/unPnbM43Qimv6cVa5RA1PimhiNJjv3TKc3GbY0LYKYieTXe1JIDUBccfgErVzNAH4TwB/aXQgRzYwrU0RL1y4Am+uKi6yG0uJ2u4uhufOIk/UjY6fnNC49Xy7WXTenpLLztXjGKYB9PqMkrtKvbvIblqyIXxybfEyEreR7KqfLEY1LBQCaTLQlJuZOAFIIKYSSbPOjFe53g0c7au0ugohmxjBFtARtrKv2A7gXQPee5sbbpBD8XS1AiXHpP5zTuPR80Yqba4Z039jsZybsPI30jXgBWIZ0vRLXM14ftto8lXLxlohN2rhXCPSGi0wA0PXE0pZIZCloQmrj0/yyLY9oOfIB+ILdRRDRzPgHGtHSdDcA96a6qrpij2uV3cXQ/M1lXHo+CSHlm9Xtl7M9f82QLMM014D9QjpHMh1vtU6nPEFZRsrmnpfDxXFgUpjSEx9JcnwABaf5EeGe4NGOvXYXQUTTY5giWmI21lWvBnCTFOLC5rrqA3bXQws3MS7d7jqmGqy9Nu0aqOm4lXAHT8QHMz32gtuZ4aopoBXnUj5jlHClbADcEym2AMAwYgIANC2x+CWFEIlNpoQQ3LWXVjYB4M+DRzv4e0C0RDFMES0hG+uqDST2lBras6phu9thlNtdEy2ObMal55vhKS8776nL+pqutjfjw5mOv+1zZpw61qz1pE70k4ZTjI0mWx6vmMUKAAwjcUjTr3YSCqEpQAjF7aaIdgP4gN1FEFFmDFNES8v1AOrchjGyuqrsBruLocWzkHHpuXSy9oasA972syLjdVNDXqM0bKWHnlWOwbSQJfsGk6tY/fHExHXDaSYGT0iJsJV4WCbCVLalES13n8/VqHQiWhiGKaIlYmNddRGA9wK4eHDtzjZD07yzPYcKy/i49E6765gsWrW9woTIKuEFx2SlEYqnn6sJ/am4kbYRcJUz6nBYoZThG9rgcGTi9gACAgCczngyNY2MbzgsoFlgjx/RhCCAT9tdBBGlY5giWjpuB2AEixuNB7b8xvX7y++55BEVPXYXRYvLI042LKVx6brh9pws3Xwxq3MhtLVvmBlb/Z6SjvDUY5oAWuLvDE0+JkeuTjYcGQ9TDqeV/Cwas8IKAASEpSyLLX5EV/1e8GhHqd1FEFEqhimiJWBjXXUNgIMALjzUdt8NhqYbtf666jua7qvYVXz3OQP+jBf+U+FZiuPSz9Ven3Vo2XXMSgtNAPCKx5nx51mjTqasWIkxM7myNaoXJcKU62qYGrUi42FKVwDDFNEkJQB+3+4iiCgVwxSRzTbWVQsk2vtimys3BLZUbdg+8ZgQAi0la+qPND3o3+A/0CWVI+t9gWjpWmrj0kVpa82odKe16WWy/ZLUMx0/63c6Mh1fqzpT32vS3L+QMR6mHEoqlchYIZXoAhRCiyssrevLiJaAR4JHO5rtLoKIrmKYIrKZU/Ns04S+H8ClB3Z+5CYpZNrvpSY1ubl8R9ORpke0Ve5rOoWSS2ZVg+ZnKY1Ll1LT3qy+Jqs9p6pjsszbb8anHg/59EB/PH1rqGZxMTVkxa+O7Iu4iiQASA1QKtHeF7KiiZUpoVlKcWWKaAoHgP9mdxFEdBXDFJGNDrS2y2Kj4kPFjspNbTW77lhT1rJxpvMdmsO5u/q64KH6h8PVjk1nwLHRBW0pjUvvq233ZHOegMCWl830moUQT5jp102t0vtSNupV6uoKlun2JYOVUGMWAIRURCTeR1oKFv+FE6W7J3i0o8nuIogogWGKyF6bNalXOKTr+x/d/v4GIbKbXeZ1eH3X1x1qPFjzyf5iLbgkVjdo7pbSuHTDV13R7arqz+bc7adVLNPx/9QdaccbnKMpIU1JlwdWYmFLuTwyGtfGf/hRBQARFVMAIKEpIA5woB/RVDqA/2p3EUSUwDBFZJMDre06gA8C6N/dsKW8tSxYMdfXKHGXlN7a+P666yo+0u0RlVm1adHS4jUiNf39HV121wEAx2uvz2rQydYrmivT8Tc9zrRU6NGUVhW/OJI8IHVdDg4l2wR7I8URABAibAFARCU6WIXQLaW4LEU0jY8Hj3bU2F0EETFMEdlpF4BqAIO3r7lh30JeqMZXW3U4eF/lrpJ3c/JfAXKLE/WjY29fsbuOcPWu8mwa60os6a3siqWtQl0KODJuKrrWOpUyTl32DSSv+euJlsQAQJOhxMoUEi8rIS0FpbgsRZSRC8Bv2V0EETFMEdniQGu7E8D7AfSsr2gpayquXbcYr9tS3Fp/pOlB/0bfwS4JJyf/FQgphGaO/kDaPS5dd3h9p0rWZ7Xn1NZXY5Gpx2Je3X3GTB+Osk6djk6+rw2NXF2ZipWYACBlYgBFLLkypSmBtDkXRHTVp4JHO8rsLoJopWOYIrJHO4BiAKN3rr/5WpHtxVJZ0KQmN1VsbzrS+Ii+yn1tF5TMeH0LLS1LZVz6mbrrs0ow28+IjBd6PR5P329qnTybcl+ORJLvcSVWbAGApiWyWWw8QAmhKU7zI5qRF8Bn7C6CaKVjmCLKswOt7S4A7wZwub6o2tda1rQ1F+/j0AzH7ur9TXfUPxKpcWzh5L8CsCTGpZetrwlJZ9qq01QbhjS3iKfnqWd1R1oYWyUvp1xjJULx5L/FfqsEAKDricUrczxMSWhq/J8s/90STe/TwaMdRXYXQbSSMUwR5V8bEt8oht698eBeTWrabE9YCK/D47uu7rbGgzWfHCjRVtm+8kEzS4xL77NtXLqUuv5W5e7u2c7zQBrNb8XSRqGf8qZfNtWgD/lSDsSuLsQOqAAAQNfGw9T4gpcUugK4MkU0i2IAj9hdBNFKxjBFlEfjE/zuAtBb4g44N1W17srXe5e4S0oONr6v7rqKe7s9orInX+9Lc5MYl/7Pto5L76ndl3GQxFRb3khfmuotMRxTj5UaMa/TGrvabmoZyS8QhkVAAwBjfKq6NR6mBDQF2D8ynqgA/Jfg0Y6s9okjosWn210A0QqzBUApgK73brx1n6EZWf3RuphqfDVVh3334e2Bk+de6f+JL4qh4nzXkG+Xh0bw9f98KXn/ysgYbt20BtetWZU89mLXefzHsdMAAIeu4T07N6O2uAgj4Qi++vQLCEVjuG3zWmyqqwYAfOWXz+PdOzch4M44JXxBJsall5UdtmVjTt1fV9XrLB0sj/QFZjpv2wWB7005Zrk04zVTj2zWzeS/bSmA1dbpoTfk5jIAUMKd/OwZ0fwSAByGKQAgLtT4czRYimGKKAsVAD4J4M/sLoRoJeLKFFGeHGhtlwDuBjDo0p3a9tqNe+ysp7m4tf7Opk8WbfTf2qUt88l/lUU+/ObB/fjNg/vxmVv2waFr2FRXlXJOqdeNh268Br9163W4ZUMrvvX8awCAl85cwK6mevz6ze342bG3AQBvXOhGXUlRToLUBDvHpQshcKzm+lk38G0N625HKJ52jdRPLFd06rG16nTy35jSvQ7ETQUAIcOfWJlyxgUAKJGYhq4JTQlYHI1OlJ3fDh7tyPuXc0TEMEWUT+sANAAYeM/GW7e5DadvtifkmiY1ual8W9OdjY/oze5rO6G0ZT/57+TlXpR5PSj1pnbFBMtL4XEYAICmshIMhkIAAE1KxOJxxC0LQgBxy8KTJ97BDWtbclqn3ePSx2p2l1qzbJqrQ4iNr8RCU4+/aBhpny3r0Xk1dAkpRP9gFACiDp8OAI6JMDX+TCl0zkwhyl4dgI/ZXQTRSsQwRZQHB1rbBYDDAEakkGJPw9Zr7a5pModmONqq9wcPNzwcrXFs6VrOf8W+fOYCtjXWznjOs2+fwbrqSgDA9sZaHO/uwZd+8SwOblyDp091YWewHg49p3NDANg7Ll13FhV1BlovzXbe5uNW2uLRO15HWgv5Gnkh5b8wrW/QBICYy2cAgNNpJT6PJsIUpFKJNj8uThFl57eDRzv4+0KUZwxTRPkRBLAeQO/hdTdt8Du9pTbXk5HH8Hivq7ut6WDtgwOlevOym/xnxi28caEbWxtqpj3n1OVePPvOWRzakthH2e0w8In9u/GZA/tQVxLAWxcvY0tdNb713Kv42tMvoLN31m64BfEZV5oGBp+x5X+Ld2pvSGvXm2rLZWlMPTZUahjmlEAe1Pvck+/LwVELAJTTqYVN3XK6Eh19Qib+FpRSE+CmvURzsRrATXYXQbTSMEwR5cftAEIAsC+48xqba5lViau45EDDr9VdX3Fvt0dUXba7nsVy7NJl1JcE4HdlvrTgwsAQvvXca7hv3y54nWlD6fD4Gydx8/rVeOnMBdSVBPD+ti348WvHcl029NhTJXaMS7cqNlZHhD5j62e9qTmKr5gpI9KVIeWv4s6RyceqjVBATRoooY1c3cqqJ1QSczohlbIgtMQG1hIagFn6DIloqgftLoBopWGYIsqxA63tNQB2Abi8vWZDVbmnpM7umrJV7aupOhz8WGVbyXvOOVA0YHc9CzVTi1//aAhfe/oFfHDPVlT40y9n6xkexVA4jJbKMsTicUghAAiYeRhhrmvw2DEuXdMcjrcqdl2c6RwJge0vp+839VO4UkKYUyqjJn7hasAKm8l2pN5ocUxqgLLCkNp4t5/QoTganWiu7goe7aia/TQiWiwMU0S5dwBADIC6ueWanXYXMx/NxavrjwQfLOjJf1EzjhPdvdg8PtocAJ4+1YWnT3UBAB5/8yTGIlF898U38KePPYk/e/yXKc//8WvH8a5NawEA2xpr8VznWfzlE0/h+rXNeal/Ylx6Xt5sku7a/WltfFNtPq3SLiB7xeFIO7ZOnUqGKWGK5OO9sZI4ACg1Cl3TEitTQgKwsHyv3iPKCQPAfXYXQbSScJ8pohw60NpeCuB6ABc8hltvLQ9utrum+ZJCyk3l25rWlmyMvtzzTOfbY/9ZBxGf9Q/tpcKha/iDuw6mHLt29dVtnN7XtgXva9sy7fPvvXZH8rbf5cSv39y++EXOYmJcutfTXJav99QDjdX9RmC4JDbon+6c9f2ae+qxc37dicHUY+vwTuRnuCFxR10NW31m8fgSVAiaVgpYgCY0KCgIzp8gmqsHgkc7/qjzC4f4VQRRHnBliii3bhj/v/Hb116/waEZuduYKE8MzXC0Ve8LHm54OFqbmPzHXqw8kUJosTyPSxdCirdq9s+431WZpekNZ8yU6BQK6K4xK3WCxDpxNnlbad7kl3n9qmR8bF9IaZqGmDItTegCSinFtSmiuWoGcHDWs4hoUTBMEeXIgdZ2B4BbAHQDwK66TTtmfkZh8Rge7/6625purX1wsFRrOWd3PSuFS1cl/Xkelz5cszcw2zk7X4mlTv7TBH4GT8p1ds3a5eRUD6V7JSIxEwAGUQwAEDKxZVXYisUm2vwER6MTzQcHURDlCcMUUe5sAuAGEF1f0VJW5Stvmu0JhajYVVxyoPG99ddX3Nvtlctn8t9S5s/zuHTDXVLS5W3qmemcTZ0qbUTif8jUIRQNxlBKq6AcGA4BwJBMZDUpExP+QipqSqEJLnoSzdvh4NGO6feAIKJFwzBFlDu3ABgBgIOt+5bVqlQm1b6aqjuaxif/iaLcbr5EeR+XfrruhhkHj7SO6F4Zt1Ja8l5zOFKuqSvWTJ8rPpxs/ZP9I1EAGNUDEgC08TAVVjFTE5rgZHSiedMB3G93EUQrAcMUUQ4caG2vBLAOQJ9DM+S6iuatdteUL83Fq+uPND0Y2OR/V5cGV0FO/isE4+PSB/M1Lj1eubUqBm3aXXTdkNr642bK6lW3X/NMvi8E0GKeTI5RF0NjJgCEdJ8OAJqe6BQMq2giTHFlimghHgge7eDfeUQ5xl8yotzYg8SF8+rW1v1rXbrTa3dB+SSFlBvLtzYdaXxYb/Hs6xJKi87+LJorrxGp7e/v6MzHe2m603W8bNuMe061vWamDMYw/dLdo2Rk8rFW63TyvhxN3Iw4E2FKT4YpMy6FZJsf0cI0AniX3UUQLXcMU0SL7EBru47E3lI9ALCnYeuyb/GbjqEZjl1V7U2HGx4xax3bOPkvB9ziRMPo2NszTttbLBfqrptxGMSG8yL1SwMh8BN4+iYfWivPJFe3RDiuAYDp8jgAwDASl1iFEY1LoQkO8iNaMA6iIMoxhimixbcegB9AeFVJfaDWX9lid0F2cxtuz/66Wzn5LwfyOS5dK2muGdK807ZuNkT0ItdYPGUV8knDnXJ/rbx09Y4pDQBQhkMbjjqU4TAFAERUzNKElOPT/Iho/g4Fj3bU210E0XLGMEW0+G4CMAYAt625brsQgn8Pjrs6+e+jl72yutvuepaLfI1LF0LKt2rap53qp0GIna+bvZOPveVM3Vut2ehPDqUQMJK3e8YCcaczsWgVgWlpXJkiWgwagPfZXQTRcsYwRbSIDrS2lwLYCuAKAGyoXL1iBk/MRbWvuvKOpo9W7S5573kHAgOzP4NmkxiX/mzOA9VA7bW+mR5ve8tKWSG74tdS9qiqdYR8SiW6PZXmSY5T7wkXq4kwFVWm0oSUCopximjh3mt3AUTLGcMU0eJqG/+/1q66zTVeh6fY1mqWuFXFLXVHgp8s2uy/7YymXHkb871c6bFf5nxcuuGpKDvvqZv2Gq013SLl37xyC9dpS0/W5JBKr411JgKX5tAwMhoHgN5owHK5EiErKkwlhUxM82OaIlqovcGjHXV2F0G0XDFMES2SA63tGoCDAHoB4JrGbRvsragwSCHlhvItjUeaHna0ePZ1cvLf/OVrXPrJ2htGpnusPK4XlVwxUwLdT6QnZfWx1TyRXL3SrgxFAaDfLEYyTMFUmpAaoHjNFNHCCQDvsbsIouWKYYpo8bQCKMX49VKrS5vW21tOYTE0w9hV1R483PCIWefk5L/5yse49GjV9goTYtr/ffa+Ek9ZuXra4Y5Nvr8aXZM37o0BwIAVUC43oJSFGOKQQpNQluDCFNGiYKsfUY4wTBEtnusARABgc9XaiiKXr8zmegqS23B79tXe2vSu2k8NlemrOflvHnI9Ll033J6TpZun3XNq18nUnHXSYzgn32+V55MniOGIBQBDohhSAnErBFPExfg0PwXBPEW0CNqDRzuq7S6CaDnS7S6AaDk40NruROJ6qUsA0N60g6tSCxRwBYpvaXhPcffopcvP9/y7GlGXquyuqVBIIbTw6A+k6XzY1DVnTv7//Lna69X6vlczPtbSr6V8kTDkk6WY1OjXol9JfpEnQqYFAMOiaLyjb0zF4YccH42u2Om35Cgzikv/9FkoMwZYFjxr21G8/8Po/bc/R/TSSQCAUVKLskP/BdLhTnt+9PI7uPLvfwUVCQFCoOajXwQgcPm7n0N8uBf+7Yfg33EIAHDl0b+Ef/vtcFSt+B0mFkoCeDeA/8/uQoiWG4YposWxBokRtHEAWFMe5PVSi6TKW115yPtRdA6+ff7lvsc8EQyW2F1TIXDpqmTgyje7yivvbcrF64vS1ppR6Q55rVDaX8seJb1NXWZ/V5NeAgDCgPNFyzmwQ0aKAaDZMWxMNHGKqBIAMGYEBAAojKm4sKQmhAYocGVqCdIMVH3g85AON1TcxKV//K9wN+9E6c0PQDo9AIC+J75uSGMfAAAgAElEQVSE4Rd/hMDeX0t5qrLi6P3R/0L5Hb8JR2Uz4qEhQGoInX4ejurVKP61/4GLX/0N+HccQvTy24BSDFKL571gmCJadGzzI1ocbQCiANBa1lRS4g5wFWWRBQPNdXcGP1m8uYiT/7LlM3pzNi5dSk17s/qay9M9fs2rsaHJ95/Q3MMTt8sdpsMbH0gMobA0DQBCjvGVKRFGXFiJNj9lCYD7tC01QojkipOyTMCKA0Ikg5RSCsqMAhkWFcPvvAhHRRCOymYAgOYugpAahNSgYpHEa40bePLrCOz7cO5/oJXjuuDRjgq7iyBabhimiBboQGu7AWA3xveWum7Vbrb45YgUUmwoS0z+W+3Z38XJf7PL5bj0vtp2z3SPbXtHpHQ+POt0pVxItdo8HgEACKcDAKIuvwQAIcNQUkkppKZgQYErU0uRsuK48JVfx7m/vAeu4DY4a9cCAHo7/gzn/uojiPWdg3/nHWnPi/VdAIRA9zf/Gy5+9Tcw+My3AQCuVdsRHx3Axb//LQT2vAdjJ5+Bo2o1dD8vPV1EGoC77S6CaLlhmCJauNUAHABiALCufBXDVI4ZmmHsrLq26XDDI2adY3uXUtNPllvpcjku3fBVV1x0VQ5leqxhVKuQ5tU37fQaKe2Aa6xTiSUI3e2EZcH0+CQASBlWSihNE1IKbjK1ZAmpofa+v0T9w19F5OIJRHs6AQDlhz6D+ke+BqOsAWNvPZn2PGXFET73JsoP/zaqPvxHGDvxK4Q6X4aQGiru/B3U3vcX8Kzdh6Hnf4Ci3Xej74kvoed7n8fYyWfy/BMuW5zqR7TIGKZoyRJC/O6k20EhxOt21jODnQBMAGgM1PjLPCX1NtezYrgNt2df3cGm22ofHCrTWzn5bxpeI1Lb1/dvXbl47ZO11/dlOm5AODYdM3sn7oe8ojRsXU1HLTibuCE1IQdGYsrhEAMhFzQtAiWgjT9oZWoVo6VDunxwNWxG6O0Xk8eE1OBdtx9jJ55OO1/3l8HVsAmaJwBpuOBu3oVo9+mUc4Zf6oBv082InD8GoRkoP/JZDP7qGzn/WVaIG4NHO0rtLoJoOWGYoqXsd2c/xV7jG/XuxfhGvTc071kveIlH3iUm/727/obKj132yZpuu+tZijzyeH0uxqWHq9vK49MsIO15Ix6auC006E8qT3IVq0Ve1iZuy76hGABcHAtA0yIQMjEcSROSWWoJio8Nwgon9m22YhGEu16GUVaHWP8FAIlrpkKnnoVRmv69kqt5J2I9nbBiYSgrjsjZ12GUN1597fAIQqeeg3fTTVBmJHHJnBCJyYG0GHQAd9ldBNFywml+lDdCiCCARwE8A2A7gBMAvgLgE0qpu8fPOQDgofHH3EKIlwG8AeD3AGhCiC8BuBbAeQBHlFIhIcQ2AH8DwAPgNICPK6X6hRA/G3+vGwEUA7hfKZXed7Iwq8bftxcA1le0sMXPRlXeqspD3nvHJ/897olggJP/xiXGpf9QxJ0PmdoijkvXHV7f8cCa/g1DJ9L+u958Trgm3/+Z5h45gLEAAASNAWPiuNY/apkALoeK4NH7AAENCpBCY6PfEhQf6UNvxxcBZQHKgmfdfrhb2tD9j5+FFRkDoGBUrkLZwUcAAGMnn0H00kkU778HmssHf9tduPS13wQE4G7eBU9LW/K1B5/6ZwSufT+EEHCv2oHhFztw8e8+Dd/222z6aZel9wD4st1FEC0XDFOUb2uRCDVPCSG+DGADgPVCiAqlVA+A+wB8RSn1r0KITyultgHJINYK4INKqQeEEP+CxAfC1wH8PYBfV0r9XAjxBwD+O4DPjL+frpTaLYS4ffz4LYv882wDEkOeyz0l7kpfWU7GUNPcBAPNdY1FD6jjfW90vTH4H+VxEfLaXdNS4NKt0v4cjEs/V3dDKFOYqoxqFa7ReDTs1RwA8IrHEcdY4rEGZ8QQURNK6BAjYQUAV6LFKmB0Q0phwAIEhBJcmlpyHJWrUHvfX6Qdr77njzOe72ndA0/rnuR938Yb4dt4Y8ZzS29+IHlb6A5Uvf9zC6yWMrg+eLTD6PzCIS73ES0CtvlRvp1VSj01fvvrANoB/AOAe4QQxQCuAfDjaZ77jlLq5fHbLwAICiECAIqVUj8fP/41ANdNes53J5+/OD9CwoHWdglgH8ZXpdqbdqySQvIvvyVCCinWl21uGp/81ymUzsl/SI5Lv7CYrynLN1aMSiNtwoWEkLteM3sm7p/36slQ69KUaIi9EwEAEYoLAOgzi+BwmEJKYQCAJjTu2Uu0+LwA9sx6FhFlhWGK8m1q145CotXvHgAfBPAtpZQ5zXMjk27Hkd3K6sRzsj1/LhoBFAEIA8DaiubmRX59WgSGphs7q64NHm54xKxzcvIfAOixXxZHon1ji/V6UtONV8p2ZJzqt+eYlfx9jnlFaX9cJv/7Xxs/lvhmPKYkAAxYRXA6TEgptbiylIBkliLKjZvsLoBouWCYonxrFEJcM377gwB+qZS6AOACgN8H8NVJ58aEEAZmoJQaBNAvhNg/fugjAH4+w1MW0xaMt/gBQENRDcPUEuY2XJ59tQebbqv71HD5Cp/8Nz4ufWAxx6UP1F2X8fi6y7Jo4rYQEP9ueZJDKVrVO4nx6ErXAGAIATidlgCAsBWNScGPKKIcYZgiWiT8pKJ8ewvAR4UQrwIoBfDX48f/EYkWwDcnnfu3AF4VQvzjLK/5UQB/PP6a2wD8wSLXnOZAa7tAop2wDwBWlzYV+5weDjsoAAFnUeDmhnfX31j5sct+WXPJ7nrsstjj0p2BpuLzjuK0azACca2krMccmbj/pOZJtlu2yguJdSfp0gFgVAvANb63b0jFTAkJLk0R5cTe4NEO1+ynEdFsOICC8s1SSn0qw/F9AL40+YBS6rMAPjvp0KZJj/3JpNsvIzGePIVS6oZJt3uxuNdMVSIRBs8AQFv9Zq5KFZhKb1Xl7d570TX4zvmX+h5zRzCw4vZeSYxL33DF62kuW+hrCSHwRtXecN3ZR9NWk/e+YvZ13KL7AOBNjzHeGAus0vs0AFAOj4aYiZBRJNzjYSqsoqYmNHA2OlFOOJG4ZvkJuwshKnRcmSLbCSFeQKJl7ut21zIHKeGptayJYapANQVW1d0ZfKBkS9HtZzTlGZn9GcuHFEKLjf5QxOOR6a5TnJN4bbsRV+nDzHedUslEdKVIc07cbnSMJW4LCe3KQCziDMDtApSyEFKxmBCSk9GJcoetfkSLgGGK8kYp1amU2pTh+E6l1HVKqUim5y1R2wAkr/2oKaoM2lcKLdT45L/GI00POVs913dKpRfSv8UFcelWad+Vb55fjNdyuktdbxU1h6YebxnQkqt+ygtPl6mbAFDqsHSf2W8BgH5lxIq5iyAlABGJhFXUkkIIrkwR5Uzm+fRENCcMU0RzdKC1XUNiJW0AADZWtpa7dCf3MVoGDE03dlTtDR5ufMSqd+5YMZP//Is4Lv2dqj1pq0kuJb2rTseSq34dljd5bdXa2BsxAJCDY1bc5wcACBmOhFUsLqEpxSxFlCttwaMdPruLICp0DFNEc1cHwAEgBgDbatZzo95lxqW73O21B5pur/vUcJm+5qzd9eTDYo1Ld1a3OUNCj0893vba1SEUv9LcyeNr4ictAJAjEQXDgd6QB1KGYxGYcV4zRZRTOlL3ZSSieWCYIpq71Zj0F15zaX3QvlIol4qcRYFbGu5uuLHyvh6/rF3Wk/8Wa1y6rru0lyq2pF17tmPS3MBT3qszKlaL8awaSYxEvzRWpKQWikUQszganSjn2OpHtED8pCKau50AhifuVPsrGm2shfKg0ltZcXvTR6r3lr7/vFOU9NldT654jUhtf//Cx6X3VF3jmHqscUwv06KJoDZcfHX/uBbtMgBAmInkdClSrKQWjkcRUxISXJkiyikOoSBaIIYpojk40NpuAFgDYBAAWsuaSjyGu2jmZ9Fy0RQI1t3Z9ImSrUWHzuhwL8vJf25xvH507J0FBUZf6Tp3rzMwOvmYDmFseD0WAgDhhv6a5QgBQNAxnBiPDocEgN5IALoWiUdVXEkhoSA40Y8od7YFj3Zwj0SiBWCYIpqbeiR+bywA2F67kddLrTBSSLGubFPjkaaHXa2e67uW2+S/xLj0H2Ah49KFkHipZk/a9Vc737KSG/Y+qrwRAKh1xQxpmbAMlwYA/fGA0vSwigpTaUJyYYootySA6+0ugqiQMUwRzc0qTPrzLlhcV29jLWQjXer6jqq9TYnJfzu7oETa0IVCtRjj0iOVe/1Tj225KLSJ2886XAoAHBKiMXo6qgy3xFgY/VYAuh5RMcQhhcbR6ES5t8fuAogKGcMU0dxsBZBs76rwllbbWAstAYnJf7c03Vb3qZFyfe05lWHT2kK00HHpHk+V63RR0+XJx2pjmtc9bMUBoNNjJK+rWmOeiAOA7L6CYVEEw4gKE3EhIQDFNEWUY9vsLoCokDFMEWVpfH+pdQCGgES7V7G7qNLeqmipKHIWBW5uuKv+pqqP9/hl3bKY/KctcFz6sbp9Kat1EkJsfdGMAECoCO7YeO5cbb2jAED2DalRLSAMIypMEYcmNEAwSxHlGMMU0QIwTBFlrxaJfTlMAFhX0VymS82Y+Sm00iQm/91TfU3p+y+4RMkVu+tZCEODZ2TgG/Mel66VbSuPCi0lUG0/mbgrHJBPW+4xAFgtLwgAkIMhhI0iGEZMiwtLSCE5fYIo96qDRzuq7C6CqFAxTBFlrxGTLuBYV97MFj+aVmMgWHu46ROlW4vuOKPDMzz7M5YmrxGu7e//8bzGpTt0j/Fa1baLk49tuiKTX0A8oXmiALDK6Et8Fo1FEXUUCYdh6pZQkpv2EuUNV6eI5olhiih7qwEkJ7fVB6oZpmhGicl/GxuPND3kXuO9oVPAKMjJf25xbN7j0i/W7k/5nKmwNKP0kjUGAC86nACAoHtMBwAZVTA9RcIw4rolLCnZ4keULwxTRPPEMEWUvVZMGj5R5StnmKKs6FLXt1fuCd7Z8LDVUICT/xYyLt3lb64ZMLwp111tf0mFAeC8V3cAQInD0gLRXguWLiyPHw4jbiipNI3T/IjyhWGKaJ4YpoiycKC13QGgBkDyj8JST4BhiubEpbvc19be0nR73UOjFcbas4U0+c+lW6X98xiXLoUmXqnf1zP52Pa34xoAxPxwD1tQALAmetyEdELoOkbggxKQEprgAAqivGCYIponhimi7ExM7VMAUF9U7XPpTq+N9VAB8zv9RTfV39Vwc/X9vYU0+c9n9DYNDj4350A1Un2Nb/L99UPwKktBaBA/sRLXTbXGT1twJE4bUEVxCKVpUjJJEeXHmuDRDo/dRRAVIoYpouxUY1K/0caq1TU21kLLRIWnovz2pnuqryn7wAWXKJnXNUn5JmNPlsx1XLrbWVF22ledbJH1Q+oNp8QwAPxCui0AWI1zgOGEGhxGj1ka07SokpAC4EA/ojyQADbbXQRRIWKYIspOE4DkdS5NxXVs8aNF01jUVHu46RMlhTD5b77j0o/XXzcy+f6O11UIAF53OQUAtOiXBQCInn7VEy+JSj1sja9McXWKKD/Y6kc0DwxTRNlZg0nDJ6r9FQxT8/Sl5/4FN/+fe3Hz330Uj/zw/0bYTB1wFzGjeOgH/x37/vcHcfjvH8TZwcRk7efOvYYDX/4YDn3tk3in/xwAYDA8jA9/87dQSNceTaeQJv/NZ1y6LG8rik26/mn7mbgBAJeLNA0AmpxDGgCgb0RdsUrjmh5WGjiAgiiPGKaI5oFhimgWB1rbJYAggNGJY+WeEoapebg43IOvvPBt/OijX8IT938NlmXhh2/9NOWcb7zagWKXH7988J/xiV3vw+d/9jcAgL997hv427s+h89e9wD+4aXvAwD+/Omv4dPXfARiGQ0pSJ38t2vJTv6b67h0h+7xvFi2Ntke2BpCkRZWKu4TRrclVJ07rGtWFHI4hH5VqqQesZijiPKKYYpoHhimiGZXBsAAYAKA3+E1fA5Pib0lFS7TiiNsRmBaJkJmGFW+spTHHzv5S7x307sAAIfWXY+nul6EUgq61BE2owiZYRhSR2f/eVwa7sU1jcvz8z8x+e/m8cl/65bc5L/5jEu/ULsvea4D0JpfFxEhgMfjzpihAY2hk0DIxKAoFroWjpuIK8VERZQvm4NHO/h3IdEc8ZeGaHbVGJ/iBwDNpQ0lYjktheRRjb8CD+7+APb+9a9h51/dDb/Ti+tX7U4559JIL2r9ieGJutThd3rRHxrEp/feg88++sf4u+e/jY/teDf+n198Cb+z/347foy8Skz+O9JwS/X9vX5Zf9Hueiab67h0X/Fm37DuSgaqbW8lvqB4SndZANASPQkZA0ZkQJN62IrCVApLK0QSLWNeJLowiGgOGKaIZlc3+U5tUWWxXYUUuoHwMB47+Us8/alv4vlHvoexWBjffeOx1JMyrMAIIbCxqhU/vPdv8C8f/HN0DV5Ala8cCsBDP/jv+L/+9XPoGS2IYXjzVu6pKL+96cM115Z98KILpVfsrmfCXMala1KXz1dvD0/c395taQBw3J0YQrHaOqOEpYsxza/rWsSKIa4ApimiPGqyuwCiQsMwRTS7NZi0WW+Ft5Rhap5+2fk8GgI1KPMUw9B03LbmOjx//vWUc6r9FbgwfBkAYFomhiOjKHYVJR9XSuEvnv57/Eb7R/HFp76C39r3cdy98SC+/MJ38vqz2KWhqLHmcPD+0m2Bw0tm8t9cxqUPVF3rmLjdHLPcrkFlXQkYOgC0yIsQmgtR3efQjQhiiCtORifKK4YpojlimCKawYHWdgGgBZMm+ZW6ixmm5qmuqAovXXgToVgYSik81fUCWstSP7sPtLbj268/CgDoOPZztDfuSBkw8a3XH8XNLdeg2OVHKBaBFBJSCIRiYawUUkixtnTD+OS/GzuFMmz94SfGpWdzbsDf7LjoKR8GEh9A618REcsjtRMxzVrl7BfC4ROm7nQaegQxWAq8aIoonxrtLoCo0DBMEc3MBcAPIDmmOuDyM0zN0/baDbh97Q247aufwC1f/hgspfChrYfxJ0/+HR47+UsAwAe2HEJ/aAj7/vcH8aXnv4mjNzyYfH4oFsa3X38U926/GwDwQNv78Mnv/T7+6Od/i3u332XLz2SnxOS/3cE7Gx9Bo6utC0raNvnPa4Rrr1zpyGpc+hu110Ynbm89mVh5etxym82eUQhNhworS9NjIibiCoJtfkR5xJUpojkSS21CFNFScqC1vQbA5wCcmzj2v247+slST3GNfVURZTYcHRl6/vJPB7ujbzbYMSPFUspU7ncPed2rSmc6LxwdiN761O85NAFclML8jc9q+s5To5GvalecW4e+iO7NDZd/B/9zzPf8kfhXQrp1qbKlNV8/A9EK90TnFw7dYncRRIWEK1NEM0tbhfI6PFyZoiXJ7/AV3Vh/Z8Mt1ff3Ftkw+U8KocdGZh+X7nIUO06UrhkAgBpL6WXnLfO01yEAYFX4mCWGQtEBEVBxWFC8Zooon7gyRTRHDFNEMyvGpN+TIqfP4dQdbhvrIZpVuaei/DabJv9lOy79TN2+2MTtTa8iPliqGQDQEn8bYiQaHxRFKiYszp8gyq+G4NEOXqdINAcMU0QzqwBgTdwJltRxVYoKxsTkv+2BO8/q8A7l630T49KfvzDTObJ0c+modFgAsLVLCeWU4ldhJ5pxHgiZakgGEBdxcJ8porxyAqiyuwiiQsIwRTSzWgDJSWm1/sqAjbUQzZkUUqwpXd9wpOlTnrXem7ryNflPxn5RHI32TzsuXZMO7eXKrREA2DygdFgWnoh71Gq9BzIKfVAWwRSK35AT5R9b/YjmgGGKaGbVmBSmKrxlXJmigqRLXd9W2dZ0JE+T/wwNnuGBf55xXHp/TTsAIKAgVx23zJcNh2hxDQkRl85hLSDjwuLKFFH+MUwRzQHDFNE0xveYqsSkMFXqCTBMUUFz6k7XNTU3Nd1e/9BopbH+bC4nus42Lt1d1OI+5yyLAcDWN+Lxs0UGmrwRYQg4h0RASC3MJEWUf9xrimgOGKaIpuca/09yMlkx95iiZeLq5L9P9BbJhpxN/nOLY3UjY29nXKESQuLlmr0xANh8HtpYuYAJYJV1Pj5q+YQ0GKaIbMCVKaI5YJgiml4Ak4ZPAIDP4eU1U7SslHvKy29r+lBNe9mHLrpEWe9iv74UQjdHf2iZ5jTBqHq3Iw5g7ZjUdRP4adSt1lqnx6IhaTFMEdmCYYpoDhimiKaXtgrl0A2XHYUQ5Vp9UUPNnU33l28P3HnWWOTJfy7dKu3t+UbGEe0eV7n+cvGaqAMCa19S+A/Lpdapt2PmmFRCDyk7Nh8mWuHY5kc0BwxTRNNL2WMKABwawxQtX0IIJCb/PeRd572pSyrHok3+K3b1lff0/jLj652qvlYBwJbjCq+7nFirnZfmmFTSCEFAcnWKKL/K7C6AqJAwTBFNrwJIHSVmSJ1hipY9TWra1sq2pjsbH0aTa3fnYk3+c6pntEikJzL1eFH5ZseY1LGlR+FSQBfN+hVXPCykpUfBdSmivPPbXQBRIWGYIppeyh5TbsOla1LTbKyHKK+cutO1t+bG4KH6h8YqjQ1n1QJH/zl0YQz0/lNaMHPqLvFM1fZY0AQcgPAZIbcIW2JIutjmR5R/DFNEc8AwRTS9YgDRiTul7gBXpWhF8jl8/hvrDzccqHmgL6A1XljIawU8cc+V7u+mvUZv9TVCE8D6l5T1rOYMVcT61IDmUxD8mCLKMxk82uGzuwiiQsFPKaLp+TBpLHrA5WeYohWtzF1W9q7GD9a2l3/oonsBk/9c+tvVw8NvjU0+VlLUql80irD1bYifG+7QuninNaB7IcClKSIbcHWKKEsMU0TT82JymHL6GKaIANT7G2oON91fviNw5KwB35wn/2lSSnP0R2bMHEu2DUoh8UL1HrWtX4nX3E65zuoSg5oPkldNEdmhyO4CiAoFwxTR9DyYFKZ8Tq/TxlqIlhQhBFpL1zUcafqUd5335i6pjNBcnu92akWXL341ZbqfWb1X1CjAGJLaWpyTI8oBXjNFZAuGKaIsMUwRZXCgtV0D4ASQvFje63BzZYpoisTkv11NdzY+IptcezqhpDn7sxLKfGH3xf4nktP9irzVeMXXpDaeQMyj9yMc1hQgOBqdKP8YpoiyxDBFlJkTU8aiew0PwxTRNJy607m35obgofqHQlXGxjPZTv5zmy8Y4Ui3NXH/eNVe7HxbacedZjwS0aHALEVkA14zRZQlhimizFyYEqbchothimgWPofPf0P9HY2JyX9Ns07+c+m67Ov7h9jEfW/VTrFqWJSccilhRRSsmZ5MRLnClSmiLDFMEWWWIUw5GaaIspSY/PeB2n3lH77oFuUzTv4rdUlnZ/e3YgDgdnhxsmJXv/OiHg/GL8Jilx+RHRimiLLEMEWUWVpwcukMU0RzVeevrznc9PHyrUWHLwrLE5vuvHK9y7gy/AYA4GLddaLxHSla4hegGKaI7MA2P6IsMUwRZZYWnBya4bCjEKJCJ4TAurINNe9e9ZDW4Ng/IpUzbfKfLiWiYz9GzAzDVdRYU9tfpJtiCJAm0xRR/nFliihLDFNEmTmB1A1uBGc0Ey2ILnV5bd21vjsaPmUE3fu6lJLxyY+XOCS6uv9BSSHlQPE+67IKKSV51RSRDRimiLLEMEWUmQtTwpSE4O8L0SJwGy59T3V70x31j4wFsG508uC/OveQuDL0/IWxqj1Fwc5RRDWDX2IQ5Z/X7gKICgX/OCTKLC1McfdQosXlc3j871p1xLu/7F5TtyriQOLXzIj+olhqwu0frRRRJdnmR5R//LwjyhLDFFFmfkzasBcAJBimiHKhLlCrv6fl49r6wF2w4qXKocEzOPDP/RHPPoduTTuzgohyh19iEGVJt7sAoiVKB1K3uOE1U0S5taV0LTaVtIoTg++cfX3gsUBv9FxYxpvsLouIiGhaDFNEmWnphximiCZT419eT77mCUDKvcQ5CkpBjH/ZrYQQSqnkIwIQSikr2c+3qqixttH/cfOV/jfEv5ts8yMioqWLYYooM4kpbQ4/wnOjDst1GVMfgEJqe7lC8oCAuhrCZv2bMC2sTX2GmHTOpHeZ7bWmFpj5vJmfIaZ9ZPr3ne6omOHB7N5HZN3PP7efez7PT3sk69Cd3WuLlJsCyPg/z6S7aY9O97Nm9b/jPBZkZ3uCyHDO1PsaAE0ELgWc1S19sbeHu/S4r5Grw0R5wy8xiLLEMEWUWdr1hDGn5XV4tEogf1fmzj210Eowv/xXWKR+oXfnzp96Hx9cPxI/sK4pfqa313i1z9IMb6XdtREREU3gAAqizNJWptSUXiYiyg1pnO3ZteunfpdTuS2Mt/k1lpdHb19dGSmLnlHx2JjNJRItd/y8I8oSwxRRZgLp3XzcPZQox6LxE9i962cBp0M5AcCCvNpyKCXUrlWN4eurZUwOd/ELDqKcMe0ugKhQsM2PKINBjDXGRPxaTBqPPhIerfVxU3iinImrN9F+7QswDDgmjlkZ9soWXpeLrX9EORW1uwCiQsEwRZTBkBi7COBNAH0Tx6SheQEU21YU0TKm66+O7m172WMYqUMm1EwNFI3l5dH6UsgXu844LosKoRnuXNdJtEIwTBFliW1+RBkogagSGFQCPRP/ATBid11Ey5FhvDi6e096kAKAWCTun+m5k1r/BFv/iBYNwxRRlhimiDJLuz7KNE1+uBAtMofj2dHde173aFrmseeWEFl1UEy0/kU2uK7EY6OXF7dKohWHn3dEWWKYIsrMwpQZ06ZpRmyqhWhZcjqfHmnbfcwj5fT7Rwm3Z2BOL5o69S+04CKJViaGKaIsMUwRZZbWKsSVKaLF43Y/OdK2+5RvpiAFAErIue8azNY/ooXi5x1RlhimiDKLYMrvB8MU0eLweCDg3v4AACAASURBVP5jdFdbp0/MnKMAANYCPqbY+kc0b6N2F0BUKBimiDIbw5RplwxTRAvn8z8+unPXOW+25yvMeWEqHVv/iOaq1+4CiAoFwxRRZuGpB6LRKK+ZIlqAosCjY9u3X8o6SAHza/PLhK1/RHPCMEWUJYYposwimDLRLxaLcWWKaJ5KSn40unVrj2euz1tIm18mbP0jykqP3QUQFQqGKaLM0oITwxTR/JSW/WBs0+b+Oa1ITVBYnJWpNGz9I5oJV6aIssQwRZRZFFMm+kUiEbb5Ec2BUhYqKr83tnHj0JxXpJKvIXL3McXWP6JpMUwRZYlhiiiztFWoUCiUdh0VEWWmVFxV13xvbN26kXkHKQCwkMXIvwVi6x9RiqHOLxxiJwZRlhimiDJLW4UaHh4e5TfXRLOzlKnq6r8bWrNmbEFBCli8ARRZYesfEcBVKaI5YZgiyiztWznLspRpmtx7g2gGSsWsxsbvhFtawgsOUkAOr5maBlv/iBimiOaCYYoosyiQvsFNLBYbsaEWooKgEI0Hg9+JrFoVdS/aa+bwmqmZsPWPVjCGKaI5YJgiyiyCDGEqGo0O21AL0ZKnVCTe3PztWGNTbNGCFACoPFwzNSO2/tHKw7HoRHPAMEWUWQiJfaZS/pCLRqNcmSKaQqmQubr127H6+rhr0V/b7jAFtv7RisOVKaI5YJgiyuD48eMKwBAAx+TjkUiEK1NEKUZja9Z+J15bay16kALsa/PLhK1/tEIwTBHNwdL5lCJaevowJUyFw2GuTBElDUfXrf+eVV2tnLl7D/tXptKw9Y+WN7b5Ec0BwxTR9PoApPyRODY2xpUpIgDAYGTDxu+joiKXQSrPo9HnIKX1T7D1j5YVhimiOWCYIppeL6asTI2OjnJlighXIps2/1CUlaX+fuSCEktwZWoS4XW54gfZ+kfLSqfdBRAVEoYpoun1AjAmHxgZGeHKFK1wPZEtWztESUnugxSQ/32m5o2tf7Q8KACn7C6CqJAwTBFNbwiJD5ak/v7+IcuyLJvqIbKXuBTetv3HMhAQeQlSifdc2itTk7H1j5aBC51fODRmdxFEhYRhimh6I0iMR0+yLEtFo9F+m+ohso84F9q+/THN7xfG7CcvnoJZmZqErX9UwE7YXQBRoWGYIppexpa+cDh8Jd+FENlJiDOhnTt/avh8+Q1S429ecGEqaaL1rzTC1j8qFCftLoCo0DBMEU1vBFM27QWAsbExhilaMYR4Z2xX288cHo/Q7Xh/JZbQRlPzIKSEamtm6x8VCoYpojkq6A8pohybmNyXEqhGRkb6bKiFKO+kPDXWtvtJp8slNPuqKNyFqcnY+kcFgm1+RHPEMEU0jePHj8eR2G/DNfn44OAgV6Zo2ZPasdG23U+7nE47gxQKu80vE7b+0dLGlSmiOWKYIprZeQCeyQf6+voYpmhZ07TXxnbvftbtcNjfYqeEtL2GxcbWP1qiLABv210EUaFZdh9SRIusC4B78oG+vr4hy7JMm+ohyindeHl0956XXIZhf5BKWGYrU5Ow9Y+WmDOdXzgUsbsIokKzRD4siZasS8jwexKJRHjdFC07huP50d27X/Xo+lIJUlh+bX6ZsPWPlgZeL0U0D0vnA5NoaerDlL2mACAUCrHVj5YVh/OZ0d273/Ro2hILLyshTIGtf7Qk8HoponlgmCKa2RVkGCc2Ojraa0MtRDnhdD012tZ23Cvl0gsuCktolSwP2PpHNmKYIpqHFfUhRTQPg0isTKX8rvT391+ypxyixeX2/Hy0re20V8oll6MSVsjKVBq2/lH+sc2PaB4YpohmcPz4cQtAN6YMoeju7r5oT0VEi8fre2J0164z3iWdVwp8096FmNT6B7b+UR68aXcBRIVoxX5IEc3BOUwJU729vf2maYZtqodowfz+x0Z37LjgtbuOWS3ppJcfwutys/WPcuxy5xcOddldBFEhYpgimt0ZTAlTADA2NsZWPypIgeJ/G922vXvpBykAgmHqKrb+Ue48Y3cBRIWKYYpodhcyHRweHmarHxWcktJ/Hd2y5UpBBClTCba1TcHWP8qRZ+0ugKhQMUwRzS5jaBoYGGCYooKhlIWy8u+Pbdo0UBBBCgDiSjIoTGNK61+P3fVQwePKFNE8MUwRza4HQByANvng5cuXGaaoIChlqcqq749t2DDssbuWuYgrmbbHG02RaP2rYOsfLYACV6aI5o1himgW4xP9OgH4Jh/v7u6+Eo/Ho7YURZQlpeKqpva7oXXrRgsqSAFcmcoWW/9ogY53fuHQoN1FEBUq3e4CiArEMQCrkNh3CgCglFKhUKjb5/M12FdW4frBD36AEydOwOv14uGHHwYAPPbYYzhx4gQ0TUNpaSmOHDkCl8uV8rzBwUF8//vfx8jICIQQ2LFjB/bu3QsAePzxx3Hq1ClUV1fj7rvvBgC88sorCIVCyXNWEkuZqr7+u+GWlkjBBSkAsMCVqbmYaP2Ln+ntNV7tU5rhrbC7JioIXJUiWgCuTBFlpxMZfl+Gh4czDqeg2W3btg333HNPyrGWlhY8/PDDeOihh1BaWoonn3wy7XlSShw8eBCPPPII7r//fjz33HPo6elBOBzGuXPn8NBDD0Ephe7ubsRiMbzyyitoa2vL14+1ZCgVs5oavxNuaYmkTaIsFHGlcYXl/2/vvsOjOs914d/vFI2kUQEVRAcDNmCMjQ3CkbAdE2cnjkmzdxL7xHvHTuK0fZLv7JKdZCfni9NDnOYkdmzca3ABbGPjhjGIMqL3thBlhHrXSJo+a73njzWiSCOhMjNryv27Ll2YWUujRwa05p73eZ81Emz9o+HhfimiUWCYIhqaBuh95RdpbW2tMaCWlDBt2jRkZV38On/mzJkwmfQfS5MnT0Z3d3e/z8vNzcWECRMAADabDcXFxejq6oIQAqqqQkqJYDAIs9kMh8OBxYsXw2w293ueVCalX51+2Sr/9MsCSRukAO6ZGg22/tEwMEwRjQLDFNHQtEAPUxf9mzl79qzTkGrSwP79+zFr1qxBz+ns7ERDQwMmT54Mm82GuXPnYsWKFRgzZgxsNhvq6+sxZ86cOFWcGKT0hWbOWh2cOjWU1EEKAFSZXiE4Fjj1jy7BB+Cg0UUQJTPumSIaAkVRQrNnzz4LYAyAc8slXV1dbp/P15aZmVloXHWpZ/PmzTCZTJg/f/6A5wQCAbzyyiu49dZbYbPZAABLlizBkiVLAABr167FzTffjL179+LUqVMoKSnBTTfdFJf6jSKlN3T5FWtCEyZomZc+O/FxAEUUTS0qCkwugGmP82xGi6lYmK1JH7YpKvY5ly8LGl0EUTLjyhTR0J0AkNv3QZfLVW1ALSlr//79qKqqwh133AEhRMRzVFXFK6+8gvnz52Pu3Ln9jjc06FPrCwsLceDAAXzxi19Ec3Mz2traYlq7kaR0B2fPWa2mSpACAE0ItvlFEVv/KAK2+BGNEsMU0dCdQoTV3NbWVmf8S0lNJ0+exLZt23DXXXfBarVGPEdKibVr16KoqAhlZWURz9m4cSOWLl0KTdPQ+3pRCIFgMFXfgO0OzL3yNa2kRNqMriSaQhxAERNs/aMLMEwRjRLb/IiGLuIKVE1NTfW8efPiXUvSW716NZxOJzweD/70pz/h5ptvxtatW6GqKp5//nkA+hCKT3/60+ju7sbatWtx9913o6amBgcPHsS4cePw6KOPAgBuueUWXH755QCA48ePY+LEicjNzT33HI888ghKSkowfvx4Y77ZmOrwz7vqLVFQgJQKUgCn+cUcW/8I2G50AUTJTnCVn2hoZs+eLQD8GYAXgP/CY3fcccf/Z7PZxhpSGKWxNt/8q982jRmDDKMriQXFM7nzF/a/jDG6jnQg3T6vZZuz2aLlTBUD9ddSqqlyLl92hdFFECU7tvkRDZGiKBLAIehDKC7CfVMUf83+q69ZZ07VIAUAKjiAIl7Y+peW3jG6AKJUwDBFNDyHgf7tVG1tbQxTFEcNvmuve9eUny8ibyxLEZzmZ4DzN/yt5g1/U967RhdAlAoYpoiGx4kIN++tra11xr0SSktC1HqvW7jekpOT2kEK4J4po4Sn/k0LT/07y6l/KckHYJPRRRClAoYpouFpBuABLm6tam1t7fT7/R3GlETpQohq78JFH1rtdpEWw4NUMEwZKdz6N5Wtfylpk3P5Mq48EkUBwxTRMAy2b6q9vf1E/CuidCFMpz2LSisysrLSI0gBgMY2v8TA1r9UxBY/oihhmCIavkMA+t0Yta6ujmGKYsJkOuEpLd1qy8wUZqNriSeVl6iEwda/lMPhE0RRwisV0fA5EWHf1JkzZ6pVVQ3EvxxKZWbzUXfp4u02my29ghTAaX6JiK1/KeG0c/kyvvlHFCUMU0TD1wR98+5F+6ZCoZDqcrlOGVMSpSKL5ZB78fW7szIy0i9IAZzml9DOt/6dZetf0mGLH1EUMUwRDZOiKBqA3QAK+h5ramriu30UFVbrPnfp4n1ZFotI25/TGgdQJLRw699Utv4lHbb4EUVR2l6kiUZpL9D/ZqmnT5+u4usJGi1rxi536eJD2ekcpAAgxDCVFNj6l1T8AD40ugiiVJLWF2qiUTgJfd/URf+Gurq63B6Pp86YkigV2GyV7sWLj2WbzUIYXYvRNMlLVFJh618y2OJcvsxjdBFEqYRXKqIRUBTFDUABkN/3WGtrK1v9aEQyM7e4F5VW2U0mBimAK1PJiK1/CY8tfkRRxjBFNHLbAeT2ffDs2bMMUzRsWdmb3ItKz9hNJuaoXlyZSl4XtP61svUvobxtdAFEqYZXKqKRUyI9WFtb2xgIBFzxLoaSV07OBz2LFtXYBRekLqJKrkwlvalFxWz9SxgHncuXHTe6CKJUwzBFNHLNAFoBZPc90NLScjj+5VAyyst/z33tdQ05RteRiHifqdTA1r+E8YLRBRClIoYpohFSFEVCb/Ub2/fYqVOnDsW/Iko2+WPWua+5ptludB2JSuMlKqWw9c9QGoCVRhdBlIp4pSIanUOI8O+orq6uyev18sUCDaigYK376qvbGaQGwZv2pii2/hlhs3P5slqjiyBKRQxTRKPjBBAEYO17oLm5ma1+1I+UGoqKX/fMu8rFIHUJXJlKXX1a/6rZ+hdzLxpdAFGq4pWKaBQURQlCb/Ur6nusqqqKrX50ESk1WTL+Nc/cud399tlRfyosfIGd4sKtf9PY+hdTfgCrjC6CKFUxTBGN3nZEWJlqaWnpcLvdvIEvAQCkVOXESau9s2d7GKSGiCtTaYStf7G0zrl8WafRRRClKl6piEbvJAAPAFvfAw0NDVydIkgZ0iZPWeWbNcvHIDUMKi9RaYWtfzHDFj+iGOKVimiUFEUJAdiCCK1+J06cOMIXBOlNyqA2bdoq/4wZgSyja0k2DFPpia1/UdUJYJ3RRRClMl6piKJjFwBL3wddLldPd3e3M/7lUCKQ0q9eNmNVYNr0IIPUCGi8aW9601v/ivxj2fo3Cqudy5f5jS6CKJUxTBFFhxNAByLcwLeuru5A3KuhBOANzZy1KjhlSijT6EqSlQqz0SWQwYTJJORitv6NAm/USxRjDFNEUaAoigZgI4DCvseOHj16VFVVvjOYRqR0By+/Yo06aZLGIDUKHEBBvdj6NyK1ACqMLoIo1fFKRRQ9ewGIvg8GAoFgS0sLB1GkCSm7g3PmvqaNH6/1G0hCw8MwRf2w9W84VjqXL+NKHlGM8UpFFD31ABoB5PY9UFVVtSf+5VC8SekKXDnvdW3cOMkgFQUMUxRJn9a/s2z9G9BzRhdAlA54pSKKEkVRJIAPAYzte6y2trbR7XbXx78qip8O/1Xz16KoqP+IfBoZFRxAQQMLt/5NZetfRBudy5cdNroIonTAMEUUXfvCv/Zr96utreXqVMpq8c+/+k1RUIAMoytJJVyZoiFh618kfzG6AKJ0wSsVURQpitIG4AAi3HPqyJEjhziIIhU1+a5Z8I5pzBjBIBVlDFM0VGz9u8gZAG8aXQRRuuCViij6PkSEEel+vz/Y3NzMMempRNR7r73uPXNenrAaXUoq4mh0Gi62/gEAHnIuX6YZXQRRumCYIoq+YwC6AfQbi338+PFd8S+HYkGIWu91131gzclhkIoVrkzRiKVv618PgCeNLoIonfBKRTElhHAYXQMACCEmCiFWXeKcMUKIfxvt11IUJQRgPYDivscaGxtbu7q6nKP9GmQsIc54Fy760Gq3C4vRtaQyhikajTRt/XvWuXyZy+giiNIJr1QUU1LKcqNrEEJYpJT1UsovXOLUMQBGHabCKqEPoeg3iOLMmTM7ovQ1yADCdNJTunhLRlYWg1SsaWzzoyhIo9Y/CeBvRhdBlG4YpiimhBA9QogcIcQGIcReIcQhIcTnwsd+d+FKkBDiZ0KI/xrkfLsQYp0Q4oAQ4rAQ4s7w46VCCEf48Z1CiFwhxL1CiFeFEG8CeF8IMV0IcTh8/r1CiDeEEO8KIRQhxP3hEpYDmCmE2C+E+P1ovm9FUVoB7EeE1aljx44pPp+vbTTPT8YwmRXP4sUOm80m+Co/DjSY+r0ZQTRiqd/6955z+TLF6CKI0g3fWaV48AG4XUrZJYQoArBdCLEWwEsAHgTw9/B5XwJw6yDn3wqgXkq5DACEEPlCiAwALwO4U0q5SwiRB6D3IlkG4GopZbsQYnqfmhYDuAqAB8AuIcQ6AD8CcJWUckGUvu8PAFzb90EppayurnbMnj37M1H6OhQHZvNRd+ni3VlWq+CbUHEi+y/sEo3Kuda/Hp/X4nCetWg5U4QQqfIXjePQiQzAFwUUDwLAb4QQB6EHjEkASqSU+wCMC+9nugZAh5Ty7EDnAzgE4OPhFa0bpZQuALMBNEgpdwGAlLJLShkKf931Usr2AWpaL6Vsk1J6AawBcEMMvm8FQBsAe98DBw8ePBAMBnti8DUpBiyWg+7F1zNIxRvb/ChWRE7Ktf4pAN4zugiidMQXBhQPd0Nvd1sYXvVpwvlJd6sAfAHAndBXqgY8X0p5AsBC6KHqt0KIn0IPXgNtKnYPUlPfz4n6xmRFUVQAbyPCPadCoZBaW1vLvVNJwGrd6158/f5si4VBKt40/i+nWEud1r+/OpcvS4cBG0QJh1cqiod8AM1SyqAQYimAaRccewnAXdAD1arBzhdCTATgkVK+AOAPAK4DcBzARCFEaficXCGGNBjgn4QQBUKILACfB7AN+jjz3FF+r33tABAA0G989oEDB3bxJr6JLSNjp3vx9YezzeaUaQNKKpzmR/FwrvXvpqSd+ucC8KzRRRClK16pKNYkgBcBLBJC7Ia+6nT83EEpj0APMHVSyobwwwOdPx/ATiHEfgA/AfArKWUA+qrW34QQB6CPJO93f6cItgJ4HvqQiNVSyt1SyjYA28LDLUY1gKKXoihuAO8DGN/3mNfr9Tc2Nu6Jxteh6LPZHD2li49nm0wMUkbhAAqKp3Otf3Ntydb696Rz+bLBOjGIKIY4gIJiRghRCKBdStkKfRhERFLK+X1+P9D5TkToCQ/vl/pIn4efCX/0nuOEPnCiV7OU8rsRnuvLA9U5ChsB3AbADEC98MDBgwe3T5gw4XqTycTNIQkkK2tLz8JFZ3JSZ196cuLKFBliWnFxYEqhNO12ns1oNRULszXL6JIG4QPwR6OLIEpnvFJRTIRb8iqht+OlNUVR2qGvhJX0PdbZ2dnd1tZ2KP5V0UCysze6F5U6GaQSgOQligySRK1/jziXL6s3ugiidMYrFcVE+Ca5V0gpE+4GglLKZyKtSsXY+9D3TfV7hX748OFtiXudTi85uevdCxfV9pu+SMbgAAoyWoK3/rkB/NboIojSHa9URHGgKEodgH0AxvU91tjY2NrR0XE0/lXRhfLy33Vfe20jg1QCkdwzRYliWnEiTv37m3P5skQLeERph2GKKH7eBhCx937//v0fJnAbScobM/Yt9zXXtDBIJRgOoKBEkmCtf10AojIoiYhGh2GKKH5OhT8K+h5oampqa21tPRD/kqig8A3P/PkdDFIJiHumKBElSOvfn53Llw10U3oiiiNeqYjiRFEUCeANAHmRju/bt2+TpmlqpGMUfVJqKB73mmfevK5so2uhyCSHgFAiM671rwPAn+P49YhoEAxTRPF1BEAj9BsTX6Strc3V3Ny8N/4lpR8pNTl+wmueOXN6GKQSGNv8KNEZ1Pr3B+fyZa44fB0iGgKGKaI4UhRFBfAyIrT6AcDevXs3a5oWjG9V6UWTITlp8mrvFVd4GKQSnOQ0P0oScWz9awHwlxg+PxENE69URPF3AEA1gLF9D7hcrp76+vqd8S8pPUgZ1KZOXe2bOdPHIJUEOM2Pkk7sW/9+51y+zB2D5yWiEWKYIoozRVE0AK8AGBPp+N69e7epquqPb1WpTyKgTpu+2n/ZZYGIExUp8WjgpilKPudb/0qi3frXAODvUXouIooShikiYxwBcAJAUd8DbrfbW1tb64h/SalLSr86Y8aq4LRpQQapJMI2P0pmIicr2q1/v3EuX5Yo97giojBeqYgMEJ7s9yqAXAD93n3fs2fP9mAwyFaOKJDSG5p1+arg5MlqptG10PCwzY9SQnRa/2oAPB7NsogoOhimiIxTBeAggHF9D/j9/sDJkyc/iH9JqcYdvGL2anXiRI1BKglJwTBFqSEKrX//41y+jO3fRAmIYYrIIOHVqTUAshBhdWr//v373W53XdwLSxndgTlzX9PGj5c2oyuhkZHcM0UpZoStfw7n8mUvxrQwIhoxhikiAymKcgbALgAlkY4fOHDgnfjctiTVuPxXznsdxcUMUkmNWYpS1fnWv+rBWv+klBqA78WxMiIaJoYpIuO9DsCGCP8eq6ur61pbWw/Ev6Rk1uG/av5aUViIDKMrodHhnilKZeHWv2mDtf4JIZ50Ll/Gm7kTJTCGKSKDKYpSB2ATgImRju/atesDVVUDcS0qabX4r77mTTF2LINUKpAitZamXA/8DM13fAytX/vCRY971qxE61c+j9av/jO6VzwY8XO1nm50/uz7aL3ndrTeewcCR/T3WLof+wva7vsSXL/9v+fO9b7/Fjyr/xG7b4SiapDWv04APzaqLiIaGoYposTwOgAVQL9BCS6Xq6e6uroi/iUlGdHkW3DtO6b8fMEglSJSbWUq65OfwdjlD1/0WGDfLvgdm1D4xCsoeno17F/6SsTP7X7oAWSUlqPo2ddQ+PjLsEybAa2nG8EjB1D4xCuApiF4ugrS74PvvTeR9bkvxuE7oqgKt/758tyNUspOAPc7ly9rNbosIhocwxRRAlAUxQXgZQDjIx3fs2fPDp/P1xbfqpJJvffaa98z5+YKq9GVUBSl2MpUxjULYcrLv+gxz9pXkf2/vgqRob8HYBpb0O/zNHcPAgf3Iuu22wEAwmqFKScXMJkgg0FIKSH9fgiLBe6Xn0XWHXdBWPhPIRkJk0mg7Irx/qUTDoM36CVKCgxTRIljC/Q73I/peyAUCqlHjx59L/4lJT4hznoXLvrAmpPDIJVq0mE0ulpbjeChfWj7t39F+79/HcHjR/qf01AHU/5YdD1wP9q+eRdcf/g5pNcLU7YdmTfdgvZv3gXzhIkQ9hwEjx9F5pKlBnwnFC1SSgmb+YfO5ctCRtdCRJfGMEWUIBRFCQJ4HsBYRBiVrihKVWdn54m4F5bATKYz3oWLNlmzs4XF6Foo+tJhNLpUVWjdXSh4+Dnkfus/0PmLH6DfHAI1hFDVcWR/9osofOwliMwsuFc+BQCw33UvCh9/Gbnf+S/0PP135Hz1O/CsW4POn/8APc/zHq/JSAjxZOPSBQ6j6yCioWGYIkosx6CPSo/Y7rdjx451HEahM5lOehaVbsnIymKQSllpsDJlLi5B5o23QAgB69yrIIQJ0tVx0Tmm4hKYisfBOnc+ACDzpo8jWHX8onN6f2+ZPA2+99/CmPsfQMh5EqHa6vh8IxQVUspWAD80ug4iGjqGKaIEEr6R76sALAD6ta21t7d3nTp1an3cC0swJvNxd+liR6bNJsxG1xILv/99M77wz07c9/Wac4+tWNGGr95bg2/cV4v7f9qInh414uf29Kj4+c+a8NV7a/C1r9bg6BEfAODxx9rwjftqsXx587lz16/vxprVrth+M6OQatP8IrEtuRmBfTsBAKGaashQECJ/7EXnmAuKYB43HqGzTgBAYO9OWKbNuOicnqf/jpx7vwOphgBNAwA9mPl9sf8mKGqEEP/duHRBu9F1ENHQMUwRJRhFUZoAvAlgQqTje/bs2d3d3Z22bzebzYc8ixfvzMrIECn78+uTn8zFb3978R//woVZeOLJyXj8icmYPNmKlf/ojPi5Dz/UhtLSLDz9zBSseGwypk6zoqdHw5Ejfjz+xGRoGnD6dAB+v4b33+vGZz+XF49vaYRSK0x1/vJHaP/uPVBrqtHypU/C+/ZryPrU56E21KH1a1+A65c/Qv4PfwEhBNTWZnT86LvnPjf3ez+E6zc/Rtt9X0LolAL73V8/d8y3dSOss+fBXDQOppxcWK+8Gm1f/yIgBKwzZxvxrdLIbAbwrNFFENHwsD2GKDG9B2ApgBwAPX0P7ty5c+3SpUu/YzKZ0urfsMW6311aejDbYkmtF9l9XX11Fhobgxc9tmhR9rn/nntlJjZvdvf7PLdbw6FDPvzgh8UAAKtVwGo1w+PREApJSCkR8GuwWIBXXnbh87fnw2JJ4P+VKbYyNeb/Xx7x8fwf/7rfY+aicRi7/KFzv7fOmo3CRyPfOyrzhqXADeeHTuR+5z9HWSnFm5TSL4T4TuPSBf1u3EtEiS1l39klSmaKonihv0M5DhGGUTQ3N7dXV1dvinddRrJm7HYvXpz6QWoo3n2nG4tLs/o93tAQRH6+Gb9/oAXf+lYt/viHFni9GrKzTbjxRju+/a06jB9vhd1ugqL4sWSJ3YDq7JtDQAAAIABJREFUhy4dBlAQAYAQ4ieNSxccNboOIho+himixLUPwE4M0O63c+dOh9vtbohvScbIsO1wL158NNts5ovrF1/sgNkM3PLxnH7HVBWoqvLjM5/Nw4oVk5GZKfDSS3o74J13jcGKxybj298pxDNPd+Cee8fi7XVd+MUvmvDCCx39nishpNjKFFEkUspNAP5sdB1ENDIMU0QJKjyM4h8AVAD9liE0TZN79ux5Q9PCu81TlC1zm7u0VLGbTHxh/f573dhe6cH//HhcxJxRXGxGcbEFc+dmAgBuusmOqir/Ref0/n7yZCvWr+/BT39aAueZAGprg/2ez3AidffFEQGAlLJbCHFP49IFKf1znCiV8UJFlMAURWkH8AIGGJVeV1fXVFdXtzW+VcVPVnaFu7T0lN2U+hOyL2nnTg9eeqkTv/zVeGRmRv7RXVBgQXGxBTU1+vT8vfu8mDYt46JzelelVFVC0/TtGcIE+P2J+FqOAZpSmxDie41LF5w1ug4iGrm02rxOlKQqAXwEwOUAGvse3L59++aioqI5WVlZ4+JeWQzZ7R+6r1tYZ4+wZSzl/fpXTThwwAeXS8Vdd1bjnnvGYuXKTgSDEj/8gd7ZOXeuDf/+H8VobQ3hT39swW/C0/+++71C/PY3zQgGgQkTLPjvHxSfe95tW92YPceGoiL9R/+VV2bivvtqMGOGDTNn2uL/jV4K2/wohUlNe6Pplus4vY8oyYl+d1onooQze/bscQB+DaAVgL/v8YkTJ4678cYbv5Eq0/1yc993L7i2KbGnI1DMfVl7OSTMlpT4O010IalpLcJkurJx6YJWo2shotFhmx9RElAUpRnASgATIx2vr69vTpWb+eaPeYdBinRcmaIUJUymrzJIEaUGhimi5FEB4ASA4kgHd+/evbOzs/NEfEuKrrFj33RffXUrgxSFcQAFpR6paU80Ll2wzug6iCg6eKEiShKKoqgAnoE+2S8j0jlbtmx5IxgM9rvJb6KTUkNh0Rueq+Z3MkjROYKTRyjFSE2tFibTfxhdBxFFD8MUURJRFKUOwMsAJkU63tPT4zlw4MBrybQXUkpNjit53XPllV3ZRtdCiUNLnr/CREMipVSFyfzlxqULku4NLyIaGMMUUfL5AMBBDHAz36qqqtP19fWO+JY0MlKqcsLENd45c9wMUnQRVZoScVY70SjIBxqXLkiKn81ENHQMU0RJJtzu9xSAEICcSOds27Ztg9vtbohrYcOkyZCcNHm17/LLvQxS1I8qTVybopQhVXWvEKb7ja6DiKKPYYooCSmK0gFgBYBxiPDvWFVVbfv27atUVQ3EvbghkDKoTZu62jdzpj/L6FooMangyhSlBqmqHcJs/nzj0gVBo2shouhjmCJKUoqiHATwLoDJkY43Nze3Hzt27M34VnVpUvrV6Zet8k+/LMAgRQMKSTNXpijpSU1TIcQdjUsX1BhdCxHFBsMUUXJbDaABQFGkg4cOHTpcX1+/Pb4lDUxKX2jmrNXBqVNDDFI0KO6ZopQQDPy46ZbrNhldBhHFDsMUURJTFMUP4BHo49Jtkc7ZsmXL+11dXc541hWJlN7Q5VesDk2apGYaXQslPpUrU5TkNHfPm023fuQBo+sgothimCJKcoqi1AJ4Hvq49H735dE0TW7evPnVQCDgintxYVK6g7PnrFYnTNAYpGhIOICCkpnm9ThN9py7jK6DiGKPYYooNWwGsAsD3H+qu7vbs3Pnzpc1TQvFtywA6A7MvfI1raRERlw5I4pEY5iiJCWDQQ+k/Hjj0gUeo2shothjmCJKAYqiaACeBtAOoDDSOTU1NQ2KorwV18LQ4b9y3usoLmaQouFRBcMUJR8ppZSenv/VvGzJKaNrIaL4YJgiShGKovQA+CuATOh7qPrZv3//gYaGhp3xqajNd9X8t0RhITLi8/UolWgcQEFJSLo6f9f8+aVrja6DiOKHYYoohYT3T60AMAGAOdI5mzdvfq+7u7s6poWIFv/V16wzjx3LIEUjo0penii5aN1dG5pvX/o/RtdBRPHFqxVRilEUZTeANwBMjXRc0zQttgMpGnwLFrxjys8X1tg8P6WDkDRzZYqShub11MBs/rzRdRBR/DFMEaWmNwAcxAADKbq6utwOh+PFUCjki+pXFbXe6xaut+TmMkjR6Ki8PFGSkMGgF6r6ieZlS3qMroWI4o9XK6IUpChKCMDjALoAFEQ6p6GhoWXv3r0va5qmRuNrClHtXbToQ6vdLizReD5KbypXpigJSFUNaa6O25s/c+Nxo2shImMwTBGlKEVRugD8BYAdAwykOHXqlPPo0aOvSzm6wWnCdNqzqLQiIyuLQYqiQ+OeKUpwUtOkWlfzby1f/MR7RtdCRMbh1YoohSmKchb6CtWAAykOHTp02Ol0bhjp1zCZTnhKS7faMjNFxOcnGomQ4DQ/Smwh56nftd7z+ceNroOIjMUwRZT6duD8QAoR6YTt27dvbWpq2j3cJzabj7pLF2+32WwMUhRdquRfKUpcwZPHV7mffOjHRtdBRMZjmCJKcYqiSACvAdiGASb8AcCmTZve7uzsPDHU57VYDrkXX787KyODQYqij3umKFEFT1c53E8/8mWfo4I3liYihimidKAoigbgGQDHMcCEP03T5IcffrjK7XbXX+r5rNZ97tLF+7IsFsGfIRQTGi9PlIBCtWePet945ZM+R0XQ6FqIKDHwakWUJhRFCQB4GEALgJJI5/j9/uCmTZv+4ff7OwZ6HmvGLnfp4kPZDFIUS6o08V1/Sihqc+NZ3/tvLvWsfZUj0InoHL4YIkojiqL0APgzgCCAsZHO6erqcldUVDwbCAS6+h6z2SrdixcfyzabRcS9V0TRooJhihKH1tne6t/y4S09zz/ebHQtRJRYGKaI0oyiKC0A/gggG/rY9H7a2tpcW7ZseTYYDLp7H8vM2upeVFplN5kYpCj2NA6goASh9XR3+ys339b10AMnja6FiBIPwxRRGlIUpRr6PaiKAdgindPc3NzucDieC4VCvqzsCveiRaftJhNzFMVHiCtTlACkz+vz79j6JdcDP9tldC1ElJgYpojSlKIohwE8BX0gRcSb7TY2ng3u3r2yZv786gzBBSmKIw1mhikylPT7A/6djm+4fvU/7xpdCxElLoYpovS2BcCr0EemX9RXZTKFCrOyXR9r72g+uHat67lQSAYMqZDSEgdQkJGkz+f3bXzvu533/9cLRtdCRImNYYoojYXvQfUWgLUApiH8M8FkChZnZbuWWiz+Y2azdvjAAV/tG2+4XmCgonhRwT1TZAzN6/F6317zI/+WDU8YXQsRJT6GKaI0Fw5UawC8D2CayRyckJ3t+qjF4j9kNmtHe8/bt89Xs3Zt14uhkOT9VSjmOM2PjKB53B7vmpU/D+zZ8VfelJeIhoJhioh6b+q7UgjNkZ3lusFsCRwwmzWl73l793rPvvVW14tcoaJYUznNj+JM6+nu8ax8+vfBowf/6HNUaEbXQ0TJgWGKiAAAiqKomZndT1ms/sfNZi0IIOLEid27vdWrVrmeDQSkN84lUhrReHmiONK6u7rcLz75YOh01XKfoyJkdD1ElDx4tSKic/bvbwyaTPJhADuh76GKGKgOH/bVr1zZ8bTPp3XHtUBKGxrb/ChONFeny/38Y39Qz575lc9R4TO6HiJKLgxTRHSRSoc7COBxAHugT/mLqKoq0PLccx1PeTxaR9yKo7TBARQUD1pHe0fPcyt+q9bV/M7nqPAbXQ8RJR+GKSLqJxyoVgDYD2A6BlihOns22Pnkk+1PdXerLXEsj9IAR6NTrKntre09z634ldZY/yefo4L7QIloRBimiCiiSoc7AOARALswSKBqagr1PPZY+9OdnWp9HMujFMc9UxRLamtzq/uZR+/Xmhv/6nNUcEIpEY0Yr1ZENKBwoFoBoALAZRjgZ0ZHh+p99NG2Z1tbQ844lkcpTIWZK1MUE2pjXaP76Ud+orW1PMJhE0Q0WgxTRDSoSoc7BOAZAO9AX6GyRDqvp0cLPPpo24uNjcET8auOUhX3TFEsBE8cPdn92F9+oHW2P+FzVKhG10NEyY9hioguqdLh1gC8BP3mvlMBWCOd5/PJ0COPtL108qR/Zzzro9TDNj+KJikl/JWb97qfXfET+P0v8j5SRBQtvFoR0ZBUOtwSwBsAXgAwBYAt0nmqCvnMMx3v7NzpeUfTJFu1aEQ0ycsTRYdU1ZB33ZoK71urfwXgVQYpIoqmiO06RESRhAPV+2Xldi+A+wA0Aoh48961a7t2traG2j/xidwvWCwiYvAiGgj3TFE0SJ/P7X752YrQiaOPAFjnc1Tw7xURRRXf+iOiYat0uLcA+BuAcQByBjrP4fCc/Mc/Op/yejVX3IqjlKDBFHF6JNFQaa7Olu4Vf347dOLoH8EgRUQxwjBFRCNS6XDvBvAHAPkACgY678QJf/Njj7U93tERqo1bcZT0NPA+UzRyofpaZ/dDD6zTmht/6XNUfMggRUSxwjBFRCNW6XAfAfBLACqA8QOd19Kiuh9+uO3Z2trgkbgVR0mNAyhopILHDh3ueeRPb0iP+6c+R8Uho+shotTGqxURjUqlw30WwC8ANECf9BexPcvnk6EVK9pWHT7s2xzP+ig5MUzRcElNk74tG7a7X3jiVWjqz32OihqjayKi1MerFRGNWqXD3QHgdwB2Q78XVcSbBEkJvPRS58b167tfDgalP44lUpLhfaZoOGQw6Pe+/vKHvnfXPgfgAZ+josPomogoPTBMEVFUVDrcPgArAKwFMA1A5kDnVlS4jz/zTPuKri61MV71UXLhyhQNldbZ0djz2F/eDuzZ/giAx3yOCp/RNRFR+uDVioiiptLhVqHf2HcFgBIAeQOdW10d7PjrX1ufdDoD++JVHyUPhikaiqByZH/Xg79Zr9bX/BHAGp+jQjW6JiJKL0LynppEFANl5fbZAP4PAA1A62DnfupTudd+5CPZt5nNgve+IwDAL9q+61SKlk43ug5KTDIY9PnWr9vo37axGsCDPkeFYnRNRJSe+NYfEcVEpcOtQB9M0QNgCgYYTAEA77zTvW/lys4n3G6tPV71UWLjyhQNROtor+tZ8efX/Ns2HgbwCwYpIjISr1ZEFDOVDncj9EC1G8BlADIGOvf4cX/TQw+1PlZfHzwWr/oocfGmvdSXlBLB40d2dD346w1qQ91+AL/yOSoajK6LiNIbwxQRxVSlw+2BvofqWQATAIwZ6Nzubs3/97+3vbJ7t+c9TZPc+5DG5MALmZSGZCDg9a5b87r7+ccUhEJrAPzJ56joMrouIiLumSKiuCkrt88E8F0AdgD1g507e7Zt3Oc+l3dHXp65JC7FUUL5Sdv3q51FZdOMroOMp7a31rhfeGKL1tTQBuDvPkfFcaNrIiLqxZUpIoqbSof7FICfAVCgt/0NOHBCUfzNDz7Y+vixY75tku/6pB1N8PKU7qSUCBw54Oh+8DebtKaGvQB+yiBFRImGK1NEFHdl5XYzgNsAfAH6pL/uwc6/7rqsqbfemnt7drZpwBZBSi0/bP9RdW1hKVem0pT0ebu87725IbBzWxeAVwG8y7HnRJSIGKaIyDBl5fYrAfxvAGYAg97A1243Zdx115hPXnZZxnVxKY4M9d/tPz5bX7hwqtF1UHxJKRE6XbXb8/KzR6S7xwXgYZ+j4oTRdRERDYRhiogMVVZuLwTwDQBzAdQBCAx2/o032q+4+Wb7Z202kz0e9ZEx/qv9/55tLLyWYSqNaO6eNt+7a98O7N0BAHsBPO1zVLgMLouIaFAMU0RkuHDb3y0A7gTgA9Ay2PmFhebsO+8c8+mJE61z41Efxd9/tv/0bFPhNQxTaUBqmhZSjlS6X31+H/z+HAAvAVjvc1RoRtdGRHQpDFNElDDKyu2TAXwTwFQAtQBCg51/0032OTfdZP9UZqYpLx71Ufz8e8fPa1oKrppidB0UW5qrs9G7bvWbwSMHTdD3Tj7sc1ScNLouIqKhYpgiooRSVm7PAPBpAJ8D0AmgY7Dz7XZTxj//c/7SWbMyrjeZBG9OlCL+T8cvaloL5jFMpSipqqHgoX0VnjUrD0ENFQDYCuAln6Ni0GE0RESJhmGKiBJSWbl9FoBvASiEvko1aMvPlVfaxt92W95nxowxT4xHfRRb3+v8VW372LmTja6Dok9tbz3rfe2ldaHTVTYAXQCeBHDE56jgCxIiSjoMU0SUsMrK7VnQx6d/HEMYoW4yQSxblrdo4cKsWywWYYtHjRQb3+38TW3H2NkMUylEhoKBwJ4dH3jXvnoSQD6A9wG87nNUeAwujYhoxBimiCjhlZXb5wO4D0Au9Il/g95vpqTEknP77fm3Tp5snReP+ij6/nfnb+s6x14xyeg6KDpCdTVHvW+8vEGtq8kF0AzgCZ+josrouoiIRothioiSQlm53Q7gMwA+CcANfaVq8M8py5558805n7LbTYWxro+i6zuuB+q6xsxkmEpymquz0bfhnXcDe7a7AdgBrAXwts9R4Te4NCKiqGCYIqKkUlZunw7gXgDTod/o1zfY+RYLTLfdlrdowYLMj2ZkmLJjXiBFxbddv6/vHjOD+9+SlPT73P5dlRt87649AqlNAuAE8JTPUVFtcGlERFHFMEVESaes3G4BcCOAuwAIAA0ABv1hlptrsn32s3k3XnGF7XqzWVjiUCaNwrdcf6zvGTOdYSrJSFVVQyeObve8/spm2dM1FkAGgFcAbPA5Kga91QERUTJimCKipFVWbi+AHqiuB9AGfTLYoCZNsuYvW5b7sSlTrFcLTlJPWN/s+nODO3/qBKProKGRUkKtqT7kXbdmg1pbHQRQAuAYgGd9jooGg8sjIooZhikiSmpl5XYB4CrorX9joa9SBS/1efPm2Sb80z/lfqKoyDI9pgXSiHyj68FGT/6U8UbXQZemtjSd9r3/1vrg0YNtACZA39P4DwA7fY6KQYfFEBElO4YpIkoJZeX2TAC3Qr/hr4Qeqga9NxUA3HBD9hU33GD/p5wcc1GMS6RhuK/7r03evEklRtdBA9NcnY2+LRs+CFRuPg1gPAALgHUA3uW4cyJKFwxTRJRSysrtRQA+B+AGAF7oY5gHZTZDLF2ac9WiRVk3MVQlhq93P9Tky5vAMJWAtJ7u1sDu7Zt9G94+DE0bC/2eUTsArPI5Ki75742IKJUwTBFRSiort08DcCeAeQA6AHRe6nNMJoibb865ctGirJvy8szjYl0jDexrPQ83+3PH888ggWidHfX+XY6t/or1xyBlDoAiAGcBvAjghM9RwRcURJR2GKaIKGWF91PNA3A39L0czQAu2X4kBHDTTfY5ixdnfzQ/38x9Owb4as/fWwK5JcVG10GA2trs9Fdu3hLYvuU0gEzowyU6AawEsIf7oogonTFMEVHKC49S/wj0yX/ZGOKQCgC48Ub7Fddfn/3RMWPMHNMdR/e6H20N5hSz5dIgUkpoTQ0nfFs2bAnu310LwAr9DQk/gNUAtvDGu0REDFNElEbKyu3ZAG4B8BkAZgBNAAJD+tyy7FllZdk3FRRYpsSwRAq71/1YWzCnsNDoOtKN1DSp1tUc8W16f2vo+OEm6EMlSqDfz+0dAO/7HBXdhhZJRJRAGKaIKO2UldvzACwFcBv0d9wbMcRQNX9+5qQlS7I/MnGi9UqTSZhiWGZau8fzeFvIXsAwFSdSU1XVefqA94O3t6rVpzug32y3BPpkzA0A1vscFa2GFklElIAYpogobZWV23MBfBT6OHUb9FA1pNaliRMteR/7WM7imTNtC61WkRnDMtPSVzxPdKj2sWONriPVyWDAFzpdtc+3fl2l2lDXDX1P1DjobbDvAtjoc1RccngLEVG6YpgiorRXVm63Qw9Vn4H+YrIJgG8on5uVJawf+1jO1fPmZZbm5Zk5yjtK/tX7VIeWnc8wFSNqW+vZ4OF9e3ybPzgKny8EfS9hMfTbCawFsNXnqOgxtEgioiTAMEVEFBbeU3UDgM8DyII+/c871M9fuDBrWmlpdunEiZa5bAEcnX/1Pe3SsvLyja4jlchAwBs6c/KAf9umPaFTSm/LXi6AAgBdAF4HsN3nqBjy33kionTHMEVE1EdZuT0LQDn0m//mQR8DPeRWp5ISS84NN9ivmTUr45rcXDPHe4/Av/ie6ZJZuXlG15EK1LaW6uCh8CqU3987xnxM+KMFwBroI86HtG+QiIjOY5giIhpAWbndCuAa6O1/U6Hvp2oGoA31OebPz5y4aFHWgilTMq7KyBBZsak09fyL/7lumWnPNbqOZCUDfs/5VagTbeGHBYBCADkAaqGHqIM+R0XIqDqJiJIdwxQR0SWEb/47C8AnACyEPuGsGUMcVgEAGRnCvGRJ9ux58zKvGTfOMottgIP7l8DzPdKWnWN0HclESgmtrcUZXoU6hkCgdxUqE/p+KBOAwwDeA3DU56gY8psCREQUGcMUEdEwlJXbiwAsAfBJ6PuqXBhGCyAAFBeb7TfcYL/68sttC/LyzONiUGbSuzvwghu2LLvRdSQ6KaXU2lvPhk5VHQvs2nZMra/tCh/qXYWyA+gB8D6AHT5HRbNRtRIRpSKGKSKiESgrt9sAXA19rPoUACr0/SfD2ndy+eUZxQsWZM2ZPj1jbn6+eUL0K01Odwdf9CAjM9voOhKR1DRNa2txhk4qx/w7th7TWprcFxzuXYUS0FehPgBwzOeoCBpRKxFRqmOYIiIahXAL4BQA10O/EXAW9AmArRjG3ioAmDzZmr9wYdacGTMy5hYUmKcKIUTUC04Sd4f+4YXVxj1mYVJTVa256XTw5PGjgR3bFK299cKJewJAEfTx5t04vwrVYkStwyWE+AqA70Nvnz0I/Y0JH4B50G8c/J9SyreEEPcCuB36PeEuA/APKeXPDSmaiCiMYYqIKErCAyvmQL9n1XXhhzuhj50elqIic3ZpafbsWbMy5hYVWWaYzcIcxVIT3t2hlX5YM2xG12EkqaohtanhZOjEsaP+7VtOyG5X3z16WdBDlIAeQjZAX4VKmoESQoh50AdhLJFStgohCgD8CcB4ALcBmAlgI/Q9i3cB+C2AqwB4AOwCcK+UcrcRtRMRAYDF6AKIiFJFpcMdBHAIwKGycns+gAUAPg5gGs63AQ5paEVrq+p5553ufQD25eSYMkpLs2bNmGGbWVJimZGdbRoTo28hcaTpqpzm7mnXmhqcwdNVpwI7tlZJj7tve14W9L1QJughfQ30VajWvs+VJD4GYJWUshUApJTt4T/6V6SUGoAqIcRp6G9SAMB6KWUbAAgh1kC/LxzDFBEZhmGKiCgGKh1uF4CKsnL7ZgCTcL4NsAR6sGrHEG8I3NOjBTZudB/duNF9FACmTrWOueqqzBlTp2bMGDfOfFlGhinl9hbJNOlx1Lwel9bUeCZUffpM8PA+5wUDJC5kh35jXQF9pXMdgP0AqlNgIp+A3t7XV9/H5CUeJyIyBNv8iIjipKzcbgYwHfqK1RLoN02VADqgT1wbNiGAOXNs4+fOtc2YPDnjssJC8zSzWVijVbNRvqy9ogqzOeVaG6XP2602N54JnXU6g0cOnFHPnhloEmQOgLHQw0YrgC0ADgCo8TkqUubCHW7zew1AmZSy7YI2v3HQh7tcBqAC59v8fgO9zc8LYAeAr7HNj4iMxDBFRGSAsnK7CcBkAPOhtyqVhA+5wh8jkpEhzHPn2iZMn54xafx4y6SCAssku91UMPqK4+vL8lVNmExJfy8u6fe51ZamM+pZpzN49OCZ0JmT7YOcngcgH3oLXz30AHUIQH0qBai+hBD3APhv6Cu2+8IPdwBYhP4DKG6DvlI3CxxAQUQJgGGKiMhg4YmAJdCnl90AfY8VoO+v6sAwx633NXasOWvOHNukqVOtk4qLLZMKCsyTEr018MtYlVTbpqSUkB5Ph9bZ3qi1tTSq9bWNodMnGtW6msGGj1ihr05mQ1+hrAGwGfpI8+ZUDlCDEUI8A+AtKeWqPo/fC2CRlPK7RtRFRBQJ90wRERms0uGWABrDHxvKyu0F0KeYXQO9JbA3+Lih75lRh/P8HR2qt7LSc7KyEid7H5s61Tpm1izbpJISy7ixY83FeXmm4uxsU4HJJAxfDZJI7PkTUlVDsrurWetoa1SbGxtDNdWNoarjTbKn61Kh14Lz4QnQw/Ih6PufTiTxEAkiorTFlSkiogQWbgecAD1cXQfgSgBm6HtpXNAnukXlB7nVCtPUqRkFU6ZYi4uLLUUFBebivDxzUU6OqSie+7BCmkneY37V8DQlAwGv9Hpc0uN2aa6ONrWxvjHkPNUYOl3VClUdyv9zM/TwZIf+ZxQEcBR6eDoNoMHnqBhWMCYiosTCMEVESS+d2n/C97KaAuBy6HtKZiK8mAN9U34Xhjh+faiEACZNsuaPG2fJLygw5+Xnm/Nzckx5drspLzvblJeVJfIyMkROtFaT/JpF/Zr55ZgOn5CaJuH3dWtej0u6ezq17i6XdHW6tI62TrW50aXW17qku2e47ZVm6PuecqH/mYQAHIe+D+g0gDqGJyKi1MI2PyJKe0IIs5QyKV7khu9ldTr88V5ZuT0T+uj1yQDmQr8fTwnOr1b1AOiG/sJ+RKQEamuDrtra4ICDMaxWmMaPt+YVF1vyxowx52ZliczMTFNmZqbIzMg4/2G1CpvVKjJ7PyKteKnSNKR3+aSUgBoKIBTyy1DIj2DQL0NBvwwG/AgE/TLo98tAIAC/3y/9Pr/0eX1aR3u32tzoUhtquxAKjWaseAb0iXv2C0sHUAVgL4BTAGqT6Qa6REQ0fFyZIqKEIYT4CoDvQw8CB6WU/xrhnC8CuB/6C1eXlPKm8MrUZ6HvRZkJ4DUp5Q/C5z8CoBT6zU5XSSnvDz/uBPAUgE8AeAjAt6G3Xy2GvrrwNSnlzph9szESHmaRBz1cTYPeFjgNrspMAAAEMUlEQVQL+rCD3nv6eAF4wr8aehEwmyGcYuadocycdTarCGVYpMligemsedbAe7fUkKb19ARkT5cfsb+GCeh/r3IAZEL/e2eCHlJPAzgBoBb6frc2rjwREaUXrkwRUUII32/mJwCWSClbw/ebieSnAD4ppawTQoy54PEFAK6F3uKmCCH+JqWsAfATKWW7EMIMYIMQ4mop5cHw5/iklDeEv/63AdillOVCiJugB62rov+dxlZ4mEXvePUjAN4O77sqBjAR+qrVZQCmQm8X7E0jAoAPesjyAIjLzWBVFTIAga4esw8wBc8fqY7Hl7+QBXpYskEP3r3BU0APSrugrzr1DgrpSddpe0REdB7DFBElio9BXzlqBQAp5UD349kG4BkhxCsA1lzw+AYppQsAhBBHoa/K1AD4khDim9B/3k2AvlLTG6Ze7vPcK8Nfe7MQIk8IMUZKOdBNVZNGpcOtAWgKf5wT3n9VCKAI+k1Sp4c/JkBffekNEyboKzL+Cz4CiNKqlgQEIGIZTAT0trzesJSpf9lz9ZugB8lWhAdDQP+70wh9RPmoRtMTEVHqYpgiokTRuxIwKCnlt4UQ1wNYBmC/EGJB+NCFQxdUABYhxGXQ2wZLpZQd4fvXZF5wnrvv01/i9yklvP+qd6XlnPBKVj70QQr50NsGC6Gvao2DHr5692VduLLV+6FC36MV6vPfvb+/8POgj7i45EqYCfqABzP0a1ekX3sDYKS6XACaoQfKegDtOL+C1+lzVPgu8fWJiIj6YZgiokSxAcBrQog/SynbhBAFkVanhBAzpZQ7AOwQQnwGeqvaQPKgByaXEKIEwKcAbBrk/DsBbBRC3AB9P9aAAxdSWXglqyP8EVFZud0MPWzlQR/CkInzKz+9j+fg/JAGe/gxG/RrT++eKGmC2oaLWw776g1ovXu9usO/uvt8eHDx6pkX4fHxHARBRESxwDBFRAlBSnlECPFrABVCCBX6OOl7I5z6eyHE5dBfYG8AcAD6fqlIz3lACLEP+t6h09BbBAfTIYRwIDyAYkTfSJqodLhV6DcQHlEbZHhQhhmAKQs+swuDjlUPMgwREVEi4jQ/IiIAQohNAL4vpdxtdC1ERESUHAYePUtEREREREQD4soUESUkIcRPAHyxz8OvSil/bUQ9RERERH0xTBEREREREY0A2/yIiIiIiIhGgGGKiIiIiIhoBBimiIiIiIiIRoBhioiIiIiIaAQYpoiIiIiIiEaAYYqIiIiIiGgEGKaIiIiIiIhGgGGKiIiIiIhoBBimiIiIiIiIRoBhioiIiIiIaAQYpoiIiIiIiEaAYYqIiIiIiGgEGKaIiIiIiIhGgGGKiIiIiIhoBBimiIiIiIiIRoBhioiIiIiIaAQYpoiIiIiIiEaAYYqIiIiIiGgEGKaIiIiIiIhGgGGKiIiIiIhoBP4flLmtAo55kZ4AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1080x648 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data_pl=data_pl.sort_values(by='percentage')\n",
    "\n",
    "# Pie chart, where the slices will be ordered and plotted counter-clockwise:\n",
    "labels = data_pl['pl_']\n",
    "sizes = data_pl['percentage']\n",
    "#explode = (0, 0.1, 0, 0)  # only \"explode\" the 2nd slice (i.e. 'Hogs')\n",
    "\n",
    "fig1, ax1 = plt.subplots(figsize=(15, 9))\n",
    "ax1.pie(sizes, labels=labels, autopct='%1.1f%%',\n",
    "        shadow=True, startangle=90)\n",
    "ax1.axis('equal')  # Equal aspect ratio ensures that pie is drawn as a circle.\n",
    "plt.title(\"Programming Languages in China, Nov 2019\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Word Cloud"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "from wordcloud import WordCloud\n",
    "wc=WordCloud()\n",
    "wc_dict = {}\n",
    "for index, row in data_pl.iterrows():\n",
    "    wc_dict[row['pl_']]=row['percentage']\n",
    "\n",
    "\n",
    "wc=wc.generate_from_frequencies(wc_dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "wc_dict['c/c++']=0.33\n",
    "wc=wc.generate_from_frequencies(wc_dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(7,5))\n",
    "plt.imshow(wc, interpolation=\"bilinear\")\n",
    "plt.axis(\"off\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(f'{year}年{month}月')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
